VictorJuiz/thesis huggingface dataset:
An idiographic approach to assess the negative effects of Instagram on mental health

Social networking sites have grown extensively over the past decade, coinciding with the growing use of internet-enabled smartphones that allow access to these sites virtually in any place and at any moment. One social networking app, Instagram, allows for passive observation of other’s photos, and extant research has connected this type of usage with myriad negative outcomes including lower self-esteem and depressed moods. Other findings, however, have produced equivocal results, indicating that use may not be harmful. The present studies investigated Instagram use on an idiographic basis to see if the true answer lies within the individual; that use is bad for specific people, but not necessarily everyone./nIn Study 1 I employed contemporaneous analyses to examine how Instagram use and a variety of mood states were associated at any given point in time. Subjects (n=51) were surveyed on Instagram use and mood eight times per day for twenty-one days. Nomothetic and idiographic network models were utilized, with strength centrality as a key measure to indicate the strength of using Instagram with other nodes in each individual network. Results indicated a significant variability in the relation between Instagram use and mood amongst the networks. The method’s potential for analysis of individual symptom patterns is further demonstrated by three exemplar participants./nIn Study 2 I examined how Instagram use and affect, jealousy, and social comparison were associated at any given point in time, as well as how they may have “driven” one another from moment to moment. Subjects (n=224) were surveyed on their Instagram use and associated variables sixteen times per day for one week. Nomothetic and idiographic contemporaneous correlations and vector-autoregressive lagged models were used. Results demonstrate significant variability in the associations and the time-lagged predictive effects of using Instagram on affect, jealousy, and social comparison. At the group level, use was not predictive of changes in affect, jealousy, and social comparison. At the individual level, however, results varied greatly. In fact, participants who used Instagram more were lower in self-esteem; those meeting diagnostic criterion for substance use disorders, posttraumatic stress disorder, anorexia, social anxiety disorder, and binge eating disorder were more vulnerable to the effects of Instagram./nTogether these findings highlight individual differences amongst social media use, identify key moderators for such relations, and most importantly underscore the importance of investigating the potential detrimental effects of social media use on an individual basis.

Advisor: Fisher, Aaron J
Mapping T-Cell Signal Integration From Synthetic, Membrane-Associated T-Cell Receptor Agonists

T-cell receptors (TCRs) recognize sparse pathogenic peptides (p) displayed in major histocompatibility complex (MHC) proteins on the surface of antigen presenting cells (APCs). Wide natural diversity of TCR clonotypes within an individual enables a robust immune response but complicates efforts to study and therapeutically control T cell activation because the pMHC ligands for almost all natural TCRs are not known. Antibodies are widely used to universally activate T cells, but unlike monovalent pMHC, antibodies activate T cells from solution by inducing extensive TCR crosslinking and have high affinity for TCR. In contrast, the physical junction between the T cell and APC is required for productive T cell activation in response a few tens of monovalent, membrane-bound pMHC that bind TCR relatively weakly. These differences suggest that antibodies short-circuit native T cell signal integration processes that confer single molecule sensitivity. We have engineered a class of membrane-associated, synthetic TCR agonists that mimic biophysical properties of native pMHC in order to activate polyclonal T cells in a physiologically-relevant manner. The modular ligand design – an anti-TCR Fab’ fragment conjugated to a DNA oligonucleotide – enables experimental control over physical parameters of ligand:TCR interactions including binding epitope, ligand geometry, and affinity. We find that, when presented on a supported lipid bilayer, high-affinity Fab’-DNA ligands activate T cells with similar potency as strong pMHC agonists, regardless of which epitope they bind. However, a short intermembrane space at binding events is necessary to maintain the native mechanical TCR triggering process. Notably, like pMHC, Fab’-DNA must be tethered to an opposing surface in order to trigger TCR; it is inactive from solution. By tuning Fab’-DNA binding kinetics to match naturally low pMHC:TCR affinities, we find roles for both on- and off-rates in coordinating the T cell activation response. The results obtained from these studies can aide in defining design principles for effective T cell therapies. Moreover, the ability of Fab’-DNA ligands to trigger TCRs in polyclonal T cells opens avenues to quantitate signal integration in human T cell populations using a membrane-associated, monovalent TCR agonist.

Advisor: Groves, Jay T.
Optics and Algorithms for Designing Miniature Computational Cameras and Microscopes

Traditional cameras and microscopes are often optimized to produce sharp 2D images of the object. These 2D images miss important information about the world (e.g. depth and spectrum). Access to this information can make a significant impact on fields such as neuroscience, medicine, and robotics. For example, volumetric neural imaging in freely moving animals requires compact head-mountable 3D microscopes and tumor classification in tissue benefits from access to spectral information. Modifications that enable capturing these extra dimensions often result in bulky, expensive, and complex imaging setups. In this dissertation, I focus on designing compact single-shot computational imaging systems that can capture high dimensional information (depth and spectrum) about the world. This is achieved by using a multiplexing optic as the image capture hardware and formulating image recovery as a convex optimization problem. First, I discuss designing a single-shot compact miniature 3D fluorescence microscope, termed Miniscope3D. By placing an optimized multifocal phase mask at the objective’s exit pupil, 3D fluorescence intensity is encoded into a single 2D measurement and the 3D volume can be recovered by solving a sparsity constrained inverse problem. This enables a 2.76 micron lateral and 15 micron axial resolution across 900x700x390 micron cubed volume at 40 volumes per second in a device smaller than a U.S. quarter. Second, I discuss designing a single-shot hyperspectral camera, termed Spectral DiffuserCam, by combining a diffuser with a tiled spectral filter array. This enables recovering a hyperspectral volume with higher spatial resolution than the spectral filter alone. The system is compact, flexible, and can be designed with contiguous or non-contiguous spectral filters tailored to a given application. Finally, the iterative reconstruction methods generally used for compressed sensing take thousands of iterations to converge and rely on hand-tuned priors. I discuss a deep learning architecture, termed MultiWienerNet, that uses multiple differentiable Wiener filters paired with a convolutional neural network to take into account the system’s spatially-varying point spread functions. The result is a 625-1600X increase in speed compared to iterative methods with spatially-varying models and better reconstruction quality than deep learning methods that assume shift invariance.

Advisor: Waller, Laura
Multiphase Flow Vertical Aerated Column with Superhydrophobic Internals using X-ray Computed Tomography and Wire Mesh Sensors

This thesis addresses the influence of superhydrophobic material on bubble dynamics within a bubble column and simulated nuclear fuel cell channels through the use of X-ray Computed Tomography and iterative reconstruction algorithms. Pressurized water reactors operate in a single-phase flow. Localized nucleation sites arise to promote convectional heat transfer to the bulk liquid. During an event of flow loss or any condition that can result in bulk liquidtemperatures exceeding saturation temperatures, bubbles will form more frequently, creating a boiling casualty called Departure from Nucleate Boiling. A Departure from Nucleate Boiling condition results from the bulk liquid temperature reaching and exceeding Critical Heat Flux. If a superhydrophobic-coated material is introduced into a fuel cell assembly, the vapor bubbles will show an affinity to the air layer in these coatings and therefore escape faster from the flow regime, resulting in a larger margin to reach Critical Heat Flux. This evaluation is made based on our findings using only an air and liquid mixture with similar characterization to vapor bubbles that would be found in a saturated system. Additionally, bubble column reactors rely on bubbly flow to promote mixing to meet chemical requirements for their applications. Superhydrophobic internals may modify the bubble regime to promote larger mixing with minimal changes in superficial gas velocity. The bubble dynamics that arise from dispersed bubble flow to slug flow can be measured by its void fraction. A superhydrophobic surface will enable bubbles to escape faster to the surface and therefore result in a void fraction value that remains lower as compared to void fraction conditions without superhydrophobic coated internals. With higher multiphase flow rates, these techniques become complex and difficult to measure. Advanced measurement techniques are required to measure void fraction in these partially opaque systems. Our findings suggests that lower void fractions are achievable with a modification of surface wall characteristics to promote superhydrophobicity. Additionally, superhydrophobic coatings do promote a transition to churn-turbulent flow without any modification to superficial gas velocity or bubble column dimensions. We show how geometric constraints, varied by adjusting the rod configuration, also play a role in localized gas holdup but not as substantial as replacing a single fuel rod with a superhydrophobic-coated rod. Lastly, advanced measurement techniques, such as X-ray computed tomography, have proven effective at providing a non-intrusive and spatial and temporal resolution of void fraction measurements in dynamic multiphase flow systems.

Advisor: Makiharju, Simo
Out-of-equilibrium dynamics and phases of matter in Atomic, Molecular and Optical systems

The past few decades have witnessed an explosive development of atomic, molecular and optical (AMO) platforms. Previously restricted to a single qubit, quantum coherent manipulation is now available across large arrays of quantum particles. This unprecedented control over many-body quantum matter has enabled the direct study of isolated quantum dynamics away from equilibrium, and has opened an entirely new landscape for exploring different physical phenomena in AMO systems. In this thesis, I explore this landscape by focusing on three different classes of dynamics: many-body localization, prethermalization, and hydrodynamics. Using a combination of analytical and numerical tools, I will discuss the stability of different out-of-equilibrium phases of matter, as well as different universal dynamical phenomena. Examples include, time crystalline order in both many-body localized and periodically driven prethermal systems, prethermal phases of matter in long-range interacting systems systems, and diffusive and superdiffusive dynamics in isolated quantum systems. At the same time, I will also discuss the experimental realization of different dynamical phenomena in AMO platforms.

Advisor: Yao, Norman
Quantum Information and Gravity: A Window

While work in the past decade has strongly cemented the connection between quantuminformation and quantum gravity, much of the research studies the connection from the perspective of applying quantum information tools to quantum gravity. In this dissertation, we aim to study the connection in both directions: not only quantum information for gravity, but how gravity may offer a window into otherwise intractable problems in quantum information theory. We begin by exploring the properties of thermal quantum error-correction codes, derived from the intersection of quantum information and many-body physics, in AdS/CFT, where the thermodynamic properties of black holes can be more tractable to study than many-body systems. We then propose a multipartite generalization and prove several properties of reflected entropy, an entanglement measure derived from studying semiclassical geometries, where again, the holographic duality of AdS/CFT enables tractable calculations. Next, we further expand on this program by demonstrating that, under a reasonable set of assumptions, holographic states saturate a large class of entanglement measures that are often intractable to compute, such as squashed entanglement. AdS/CFT may therefore provide a useful arena by which to study various quantum information-theoretic quantities that may be too complicated to understand in generic quantum systems. We then turn our focus to generalizing graph-theoretic techniques for studying entanglement in quantum gravity to quantum information, more broadly. We do this in a systematic fashion, in increasing order of generality (graphs to hypergraphs to topological knots), showing that they capture broader swathes of quantum entropies. We complete this line of study with a mathematical investigation of random tensor networks with non-trivial link states, in which we take a computational tool common in condensed matter and quantum gravity, and generalize the tool to capture entanglement properties for a broader class of quantum states.

Advisor: Bousso, Raphael
Microbial Population Dynamics in Spatial Structure

Microbes proliferate and migrate to take over territories. The dynamics of population growth canbe classified by the rate of proliferation and migration. When proliferation is predominant, the population density tends to saturate, and cells form expanding clusters. On the other hand, when migration is more active than the timescale of proliferation, the populations get almost well-mixed like a liquid culture in a shaken test tube. Both extreme cases have been extensively studied in previous research. However, the intermediate regime, where proliferation and migration consort with each other, has not been understood well. With this thesis, I attempt to provide an overarching insight into the interplay of proliferation and migration using microfluidic experiments and computer simulations. In Chapter 2, we show that the balance of proliferation and diffusion results in the sharp transition between two density states, gaseous and jammed states, using a newly-developed microfluidic device named microfluidic panflute. The density dependence of the diffusivity is shown to be fundamental to producing bifurcating behaviors with hysteresis. We further discuss the ecological impact of the density transition on invasion resistance. Chapter 3 characterizes the clone size distribution of jammed populations by fluctuation tests and lineage tracing with microfluidics. We show the characteristic power-law decay of the site frequency spectrum. We further discussed applying our results to cancer research: the site frequency spectrum can be reconstructed by sampling tumors spatially. In chapters 4 and 5, characteristic behaviors of jammed and gaseous populations are discussed. Chapter 4 shows the impact of the shape of physical boundaries on the population dynamics in a jammed state. In chapter 5, gaseous populations in various types of flow are investigated. This thesis contributes to the understanding of microbial population dynamics in spatial structure. Also, experimental techniques developed in this thesis, especially microfluidic systems, have the potential to be a platform for microbial experiments to investigate the ecological and evolutionary dynamics under spatial constraints.

Advisor: Hallatschek, Oskar
Negative Capacitance Field-Effect Transistor Design and Machine Learning Applications in Compact Models

With the scaling of the transistor, fabrication of an actual device and modeling of an ultra-short channel transistor becomes more and more challenging. Dr. Salahuddin proposed a negative capacitance field-effect transistor (NCFET) in 2008. By utilizing the ferroelectric negative capacitance region with proper capacitance matching a ferroelectric layer with a dielectric layer, the overall effective oxide thickness could be further thinned down without affecting much of the carrier mobility.A technique of optimization of an NCFET will be proposed in chapter 2. By utilizing process techniques like mask oxidation, a non-uniform interfacial layer can be formed to create a more uniform metal-oxide-semiconductor capacitance along the channel (Cmos). The overall capacitance matching of an NCFET can be improved because of a uniform Cmos profile. Chapter 3 will introduce a simulation scheme of NCFETs variation due to dielectric grains within a ferroelectric film. This scheme can be applied to the future estimation of NCFETs variation given the grains' size and the ferroelectric parameters. The effect and compact modeling of the polarization gradient effect will be demonstrated in Chapter 4. With the feature of polarization gradient effect in an NCFET compact model, the characteristics of an NCFET can be better captured, such as negative drain resistance and negative drain-induce barrier 2 effect (DIBL). Energy analysis of an NCFET will be presented in Chapter 5. The consistency between TCAD energy calculation by the integral over the grids with the Landau equation and power consumption calculation from the circuit is shown in detail. Negative capacitance benefits on FinFET and gate-all-around (GAA) FET will be presented in chapters 6 & 7, respectively. Baseline devices of a FinFET and a GAAFET are made in technology computer-aided design (TCAD) and are calibrated to International Roadmap for Devices and Systems (IRDS) tables. NC parameters are also extracted from an experiment on metal-oxide-semiconductor capacitance (MOSCAP). How many nodes NC extends the baseline will be discussed. A compact model of an anti-ferroelectric on an NCFET will be presented in Chapter 8. Potential applications of machine learning will be illustrated in Chapters 9 & 10. Machine learning-assisted parameter extraction will be presented in Chapter 9. In the long run, using machine learning-assisted models as an alternative to the conventional equation-based compact models will be shown in Chapter 10. In the end, Chapter 11 will conclude chapters and propose some future work.

Advisor: Hu, Chenming
An atomistic understanding of exciton-phonon coupling and nonradiative processes in semiconductor nanocrystals

Semiconductor nanocrsytals (NCs) have been of much interest over the past several decades due to their highly tunable optoelectronic properties, which make thempromising materials for applications ranging from solar energy conversion to quantum information. These optoelectronic properties depend significantly on electron-hole and exciton-phonon interactions, which are enhanced in NCs due to quantum confinement. A fundamental understanding of these interactions as well as processes, such as exciton decay and dephasing, is key to developing rational design principles for NCs with decreased thermal losses and increased quantum yields. Yet the description of excited carriers in NCs remains a great challenge for modern computational science. In this dissertation, we address this gap by developing a unified, atomistic model to accurately describe excitonic properties and dynamics in experimentally relevant NC systems with thousands of atoms and tens of thousands of electrons./nWe develop an approach for calculating exciton-phonon couplings (EXPCs) and validate them by computing the reorganization energy, which is a measure of EXPC and is relevant for optical Stokes shifts, charge transfer processes, and NC-based device efficiencies. This microscopic theory allows us to delineate the dependence of the reorganization energy on NC size and structure as well as on phonon frequency and localization, resolving questions regarding the role of quantum confinement on EXPC. Additionally, we use this EXPC framework to perform quantum dynamics simulations of hot exciton cooling to address the longstanding controversy of the phonon bottleneck, which hypothesized slow nonradiative relaxation of hot carriers to the band edge in confined semiconductor nanostructures. Contrary to the phonon bottleneck but in agreement with recent experimental measurements, we find that cooling in CdSe NCs occurs in tens of femtoseconds. We show that this ultrafast timescale is governed by both electron-hole correlations and efficient multiphonon emission processes. Finally, we employ these tools in collaboration with experimentalists to understand lattice heating and polaron formation, photoluminescence, and charge trapping and transfer in various NC systems. The atomistic theories and calculations presented in this dissertation bridge our understanding of molecular and bulk systems to provide fundamental insight into exciton-phonon interactions and nonradiative processes at the nanoscale.

Advisor: Rabani, Eran
Phosphonated Xanthene Fluorophores for Live-Cell Imaging Applications

Since the original synthesis of fluorescein in 1871, the use of xanthene fluorophores has remained ubiquitous in biology, medicine, and chemical biology. The wide utility of fluorescein and related xanthene dyes is due, in part, to their high brightness and wide range of colors available with simple modifications to the terminal and bridgehead atoms of the xanthene fluorophore core. By comparison, substitution of the pendant carboxylate has remained relatively underexplored. The identity of the substitution at this 3- position can have profound effects on the properties of xanthene fluorophores. We envisioned installation of a biologically relevant phosphonate functionality may provide access to fluorophores with unique properties, such as enhanced water solubility and opportunities for functionalization. Herein we will discuss the first syntheses of novel phosphonated xanthene fluorophores, their associated spectroscopic properties, and the utility of these dyes for both intracellular imaging and membrane potential sensing in living cells.

Advisor: Miller, Evan W