VictorJuiz/thesis huggingface dataset:
Interface engineering in inorganic-absorber nanostructured solar cells [electronic resource]
Keywords: Materials Science and Engineering.

The focus of this work is variants on the dye-sensitized solar cell (DSSC) that employ inorganic materials as the light absorber, replacing the organic dye molecules used in DSSCs. Such DSSC-inspired devices are emerging technologies in the broader class of thin film solar cells, and include quantum-dot sensitized solar cells (QDSSCs) and perovskites solar cells (PSCs). Quantum-dot sensitized solar cells employ semiconductor nanocrystals, or quantum dots, as the light absorber. The band gap of quantum dots varies with size, allowing for a tunable absorption onset in these devices, among other benefits. PSCs, in which the absorber is CH3NH3PbI3, or variants thereof, with the perovskites crystal structure, first attracted attention in 2012 and have shown an unprecedented rise in efficiency to current record values of 20.1%. QDSSCs and PSCs can be fabricated completely from solution processed materials that can be low-purity, contrasting favorably with the industrial standard, silicon solar cells, which require expensively-processed, high-purity silicon. This tolerance to defects is partially due to the nanostructured design of some PSCs and all QDSSCs, in which a nanostructured bulk heterojunction is formed between the electron-transport material, the absorber, and the hole-transport material. However, the high interfacial areas involved in such designs leads to high rates of interfacial recombination, causing losses in photocurrent, and limiting device efficiency. In this work, I will present methods to reduce interfacial recombination in these inorganic-absorber nanostructured solar cells though surface modifications. In QDSSCs, these include growing ultra-thin insulating metal oxide films by atomic layer deposition (ALD) at the interface and controlling of the nucleation and growth of the inorganic absorber. These studies provide insight into the working mechanisms of QDSSCs, through a combination of the highly-controlled nature of ALD, where films can be grown a single atomic layer at a time and an interface can be atomically engineered, X-ray absorption measurements of interfacial geometric and electronic structure, and detailed studies of the resulting solar cell performance. I will also detail the use of ALD to grow entire material layers in perovskites solar cells, both ALD TiO2 as the electron-transport material, and ALD NiOx as the hole-transport material. Despite their high efficiencies, PSCs are unstable and rapidly degrade when exposed to moisture or excessive heat. The use of ultra-conformal inorganic layers grown by ALD to cap the perovskites absorber, instead of the currently-employed organic layers, has the potential to improve the stability, and thus efficiency, of perovskites solar cells.
Intrinsic retroviral reactivation in human preimplantation embryos and pluripotent cells [electronic resource]
Keywords: Genetics.

Endogenous retroviruses (ERVs) are remnants of ancient retroviral infections, which comprise nearly 8% of the human genome. The most recently acquired human ERV is HERV-K (HML-2), which repeatedly infected the primate lineage both before and after the divergence of humans and chimpanzees. Unlike most other human ERVs, HERV-K retained multiple copies of intact open reading frames (ORFs) encoding retroviral proteins. However, HERV-K is transcriptionally silenced by the host with exception of certain pathological contexts, such as germ cell tumors, melanoma, or HIV infection. Here we demonstrate that DNA hypomethylation at LTR elements representing the most recent genomic integrations, together with transactivation by OCT4, synergistically facilitate HERV-K expression. Consequently, HERV-K is transcribed during normal human embryogenesis beginning with embryonic genome activation (EGA) at the 8-cell stage, continuing through the emergence of epiblast cells in pre-implantation blastocysts, and ceasing during hESC derivation from blastocyst outgrowths. Remarkably, HERV-K viral-like particles and Gag proteins are detected in human blastocysts, indicating that early human development proceeds in the presence of retroviral products. We further show that overexpression of one such product, HERV-K accessory protein Rec, in a pluripotent cell line is sufficient to increase IFITM1 levels on the cell surface and inhibit viral infection, suggesting at least one mechanism through which HERV-K can induce viral restriction pathways in early embryonic cells. Moreover, Rec directly binds a subset of cellular RNAs and modulates their ribosome occupancy, arguing that complex interactions between retroviral proteins and host factors can fine-tune regulatory properties of early human development.
Invariance for perceptual recognition through deep learning [electronic resource]
Keywords: Electrical Engineering.

The brain implements recognition systems with incredible competence. Our perceptual systems recognize an object from various perspectives as it transforms through space and time. A key property of effective recognition is invariance to changes in the input. In fact, invariant representations focus on high-level information and neglect irrelevant changes, facilitating effective recognition. It is desirable for computational simulations to capture invariant properties. However, quantifying and designing invariance is difficult, because the input signals to a perceptual system are high dimensional, and the number of input variations, conceived in terms of separate dimensions of variation, such as position, rotation, scale can be exponentially large. Natural invariance resides in a subspace of this exponential space, one that, I argue, can be more effectively captured through learning than through design. To capture perceptual invariance, I take the approach of modeling through deep neural networks. These models are classic AI algorithms. The deep neural network is characteristic of composing simple features from lower layers into more complex representations in higher layers. Going up in the hierarchy, the network forms high-level representations which capture various forms of invariance found in natural images. Within this framework, I present three applications. First, I investigate position-preserving invariance properties of a classical architecture, the convolutional neural network. Indeed, with convolutional networks, I show results surpassing the previous state-of-the-art performance in detecting the location of objects in images. In such models, however, translational invariance is designed, limiting their ability to capture the full invariance structure of real inputs. To learn invariance without design, I exploit unsupervised learning from videos using the 'slowness' principle. Concretely, the unsupervised learning algorithm discovers invariance arising from transformations such as rotation, out-of-plane changes, or warping from motions in video. When quantitatively measured, the learned invariant features are more robust than ones that are hand-crafted. Using such invariant features, recognition in still images is consistently improved. Finally, I explore the development of invariant representations of number through learning from unlabeled examples in a generic neural network. By learning from examples of 'visual numbers', this network forms number representations invariant to object size. With these representations, I illustrate novel simulations for cognitive processes of the 'Approximate Number Sense'. Concretely, I correlate simulations with deep networks with the sensitivity of discrimination across a range of numbers. These simulations capture properties of human number representation, focusing on approximate invariance to other stimulus factors.
Investigating strain hardening by simulations of dislocation dynamics [electronic resource]
Keywords: Mechanical Engineering.

Materials deform, though different materials do not deform in the same way. They should not be expected to, as they can have very different underlying structures. In ductile metals, deformation occurs in three stages: elastic deformation, plastic deformation, and fracture. Elastic deformation is defined as recoverable deformation. Ductile metals are elastic for small deformations. This is in contrast to plastic deformation, which is unrecoverable deformation. Dislocations are thought to be the carriers of plasticity in metals, and as such play a key role in material deformation. This thesis presents simulation results that explore particular aspects of plasticity, specifically work hardening and cross-slip, at the mesoscale and microscale, respectively. In order to obtain these results, a number of mathematical and numerical advancements were made to improve the efficiency of the simulations and the resulting physics. With the code enhancements, a variety of novel results were obtained. The implementation of an expanded and more powerful 2D Dislocation Dynamics (DD) code, named DD2D, has resulted in efficiency gains of an order of magnitude or more. The advances included mathematical subtleties (implementing nonsingular stresses and a correction for conditional convergence), physical models (adding sources, obstacles, and sessile junctions), and numerical improvements (implementing different integrators and utilizing subcycling). Because of these, a large number of different simulations in DD2D were run and the stress-strain curve results are presented. These results are used to investigate the hardening behavior and propose a tensile yield surface for various configurations of glide planes and compare them to what Schmid's law predicts. Improving the algorithms of an atomistics code, MD++, resulted in the ability to explore stress regimes previously unable to produce results. A new "Reparametrization with Trimming" algorithm allowed the energy barrier for cross-slip to be calculated under high applied stress configurations at temperatures of 0 K. An equilibration algorithm allowed decreased equilibration times at finite temperature by an order of magnitude, greatly increasing the number of temperature and stress configurations that could be investigated. The 0 K simulations of cross-slip explored the effect of different stress components on the energy barrier for cross-slip. Two different theoretical mechanisms were explored: the Friedel-Escaig (FE) mechanism and the Fleischer mechanism. Over three hundred cross-slip simulations were run at different stress configurations at 0 K. The data were fit to 1D curves (one for each mechanism) using an "effective stress, " τ*, comprised of a combination of the applied stresses. Finite temperature simulations produced results used to find the cross-slip rate coefficient that, together with the energy barrier fit, was implemented into a 3D DD code.
Investigating the Leukemogenic Properties of DNMT3A R882H in Human Cells
Keywords:  Department of Biology
Biology
Thesis

Acute myeloid leukemia (AML) is a clonal malignancy of bone marrow progenitors that are arrested in their ability to mature, and for which clinical outcomes have not improved in over 30 years. Mutation in DNA methyltransferase 3A (DNMT3A), an enzyme responsible for catalyzing de novo methylation at CpG sites throughout the genome, is present in approximately 20-25% of normal karyotype AML cases, with more than half of all mutations altering R882 within the catalytic domain. We have recently shown that DNMT3A R882H occurs frequently in mutated but otherwise normal preleukemic hematopoietic stem cells, but little is known regarding its mechanism of action in contributing to leukemogenesis in human cells. Our studies thus focus on characterizing the biological phenotypes associated with DNMT3A R882H in AML cell lines and cord blood-derived hematopoietic stem and progenitor cells (HSPCs) with regard to proliferation, cell survival, immunophenotype, and differentiation. Interestingly, we found that the R882H mutation causes a time-dependent reduction in mature myeloid antigen expression and decreased apoptosis in THP-1 cells, with minimal effects on cell proliferation, mitochondrial mass, and ATRA-induced myeloid differentiation. Lentiviral transduction of DNMT3A R882H into FACS-purified human CD34+ stem and progenitor cells also resulted in increases in both the Lin-CD34+ percentage and fraction of CD34+CD38- HSPCs, consistent with a role for the mutant in retaining stem cell character. In addition, we found that mutant DNMT3A conferred time-dependent and reversible growth factor independence in TF-1 cells. Transcriptional profiling of these cells revealed upregulation of genes including ANGPT1 and CD36, which are also expressed in primary DNMT3A-mutated AML samples from The Cancer Genome Atlas Network (TCGA). These findings provide evidence for the role of mutant DNMT3A in maintaining a primitive cell state, enhancing cell survival, and promoting growth factor independence, and together offer insight into the mechanisms by which the mutation contributes to leukemogenesis.
Investigating the mechanisms for phototaxis in the cyanobacterium Synechocystis sp. PCC 6803 [electronic resource]
Keywords: Bioengineering.

Signal transduction in bacteria is complex, ranging across scales from molecular sig- nal detectors and effectors to cellular and community responses to a stimulus. The unicellular, photosynthetic cyanobacterium Synechocystis sp. PCC6803 transduces a light stimulus into directional movement known as phototaxis. This single-cell response occurs via a biased random walk toward or away from a directional light source, which is sensed by intracellular photoreceptors and mediated by Type IV pili. In this dissertation, I will discuss how I have used the combined manipulations of the light conditions, genetic perturbations, quantitative, single-cell measurements, and a reaction diffusion model to derive simple guiding principles across length scales for cell motility. I first demonstrate that cells indirectly interact with each other via a secreted substance that enhances their mobility, These intercellular interactions re- sult in the dynamic spatial organization of the multicellular community, which do not appear to require changes in individual behavior. I then show how movement directionality of the single cell is determined mainly by the light signal, and is the result of a polarization of pilus pulling forces along the light axis. Finally, I will reveal the newly identified role of the photoreceptor TaxD1 in enhancing movement direction- ality, in addition to its previously shown role in promoting positive phototaxis. Our broadly applicable framework can also be used to dissect similar complex regulatory networks that effects robust responses from input signals.
Investigation of the switching mechanism in hafnium-oxide-based non-volatile resistance change memory [electronic resource]
Keywords: Electrical Engineering.

In recent years, an increasingly complex memory hierarchy has emerged to enable the scale, availability, security, and reliability demanded by new modes of content creation and consumption. However, the overall efficiency and performance of many memory architectures is limited by the latency-power-endurance gap that presently exists between DRAM and NAND FLASH technologies. Resistive Random Access Memory (RRAM) is a high density, low power, non-volatile memory technology that can fill this gap. Despite great interest and numerous modeling attempts, however, fundamental understanding of the RRAM operation mechanism through direct observation is lacking. In this work, first the merits of RRAM in fulfilling evolving memory technology requirements are explored and the challenges to its adoption are reviewed. Next, a novel characterization methodology, based on a highly scaled, membrane-supported lateral device structure is presented. This test device is optimized for in-situ electron microscopy and spectroscopy, while also capturing the fundamental physics governing a conventional, technologically relevant RRAM cell. The new processing techniques developed for the fabrication of sub-10 nm TiN-HfOx-TiN lateral devices on 50nm-thick membranes are described in detail. In the second part of this work, the test devices are thoroughly studied using a comprehensive set of ex-situ and in-situ characterization techniques, in order to distinguish the fundamental physical mechanisms based on direct observation of the electrical, structural, and spectral data.
Investigation on diagnostic biomarkers and protein-protein interactions by using giant magnetoresistive biosensors [electronic resource]
Keywords: Mechanical Engineering.

In the past decade, our research group has been developing giant magnetoresistive (GMR) biosensors and demonstrated that this sensor platform has great potential for application to many fields of nanomedicine, especially diagnostics and drug development. In this dissertation, I present major development and several new applications of GMR biosensors. First of all, the history of magnetic biosensors and GMR biosensors are introduced. Then, a new technique to longitudinally monitor immune response via antibody isotypes is described. This technique is used, in conjunction with bioluminescent imaging, to measure both firefly luciferase (FL) specific and total antibody response, and to find the upregulated IgG2a response in the regression mice. Cytokine measurement shows interferon-gamma signature in the regression mice. These results indicate that the immune response is predominantly involved with T-helper-1-cell-mediated immune response. Secondly, the use of protein and peptide microarrays for autoantibody detection is demonstrated. System lupus erythematosus is an autoimmune disease, characterized by the existence of autoantibodies. A chemokine score was previously proposed to assess disease severity. The correlation between autoantibodies measured by the microarray and the chemokine score is found, and the reactivity of autoantibodies to histone 2B peptides in chemokine high patients is higher than in chemokine low patients. Thirdly, a new kinetic assay using GMR biosensors is presented. The current gold standard, Surface Plasmon Resonance (SPR) is sensitive to changes in pH and salt concentration and is typically single-plex in nature. The GMR biosensor platform is insensitive to pH and salinity, and has an added ability to multiplex. By using magnetic nanoparticles conjugated with proteins and microfluidic chips, the interactions between programmed cell death 1 (PD-1) protein and its ligands are measured utilizing bivalent interactions and a Langmuir isotherm binding model. Lastly, the use of GMR biosensors as point-of-care (POC) devices is demonstrated in a Eigen Lifescience platform.
Iterative convex methods for control [electronic resource]
Keywords: Mechanical Engineering.

This thesis examines ways to leverage the techniques of convex optimization for control problems (and other problems) that are not necessarily convex by using iterative procedures. Often we can find very good solutions to hard problems by solving a series of simpler problems. As the techniques for convex optimization have improved over the past couple decades, the qualifications for simple problems have expanded dramatically allowing for these simple steps to be remarkably complicated. By leveraging this increased complexity we develop algorithms that are more efficient and capable of handling more complex models. In the first chapter of this thesis we examine the problem of trajectory optimization, in particular the minimum-time traversal of a fixed path. This is a problem that arises in machining, automated racing, surveillance, and other applications. We explore a change of variables that makes the problem convex. We exploit the structure of the problem to efficiently find solutions. This speed allows the algorithm to be used in online settings as part of model predictive control (MPC) loops. The algorithm can also be used to rapidly evaluate different trajectories to identify the fastest one. This evaluation splits the minimum time trajectory problem into a series of fast trajectory evaluations. In the second section of the thesis we examine a technique called the convex-concave procedure (CCP) which addresses difference of convex (DC) problems. This iterative procedure finds local minima of DC problems by solving a sequence of convex problems. We present a number of extensions to this algorithm to allow a much wider range of problem classes to be considered, including a vector form of the problem and extensions to address large scale problems. We then present a series of examples to highlight various aspects of these algorithms. In the last section of the thesis we leverage CCP to address the antagonistic control problem. Whereas a typical control problem attempts to minimize an objective, the antagonistic control problem maximizes an objective. This simulates an aggressor taking control of a system to do it harm. Having knowledge of how and when harm can be done to a system, allows for better defense of the system. We also demonstrate how the S-procedure can be used to get an upper bound on the negative behavior to pair with the lower bound provided by CCP.
'La gran dolor que llengua no pot dir' [electronic resource] : ausiàs March and the poetics of private pain
Keywords: Iberian and Latin American Cultures.

The present dissertation explores how the poetry of Ausiàs March (1400-1459) problematizes the view of fifteenth-century Iberian literature as part of a linear transition from the medieval to the early modern period. More specifically, I examine notions of body, pain, and subjectivity that emerge in the lyric poetry of the late medieval Crown of Aragon and trace their trajectory through the 128 cants of the Valencian poet and into the literary milieu of sixteenth-century Castile. I argue that the unique way in which March draws upon so-called medieval tropes and source material, the way his poetics theorize on the essence of private pain before pain was private, paradoxically fashions what so many scholars point to as his strikingly modern, subjectively emotional "self." Focusing on the themes of language, love, community, and pleasure and pain, my first chapter excavates March's complicated relationship with his troubadour predecessors, focusing on what he takes from the Provençal tradition and what he abandons. In the second chapter, I examine the work of Giorgio Agamben, David Bakan, Ariel Glucklich, and Elaine Scarry to offer a new reading of March's verses that focuses on his treatment of bodily pain and what it implies vis-à-vis theories of the self. Chapter three is a close comparative analysis of March's original cants and their most widely disseminated sixteenth-century Castilian translation, that of the Portuguese Jorge de Montemayor (1560); in this final chapter, I pay special attention to the ways in which Montemayor transforms and even eliminates March's frequent presentation of the poetic self, the body, and pain. By situating my study within a trans-linguistic (and trans-national) framework, I am able to arrive at a more nuanced understanding of textual constructions of subjectivity and experience in fifteenth- and sixteenth-century Iberia.
Lagrangian Tori in R4 and S2xS2 [electronic resource]
Keywords: Mathematics.

We study problems of classification of Lagrangian embeddings of a torus in a symplectic 4-manifold. First we complete the proof of a claim that all Lagrangian tori in R^4 are isotopic. Next we present a construction of Lagrangian tori and Klein bottles in monotone S^2xS^2. Finally we show that all monotone tori may be produced from such a construction, and outline a new approach to the problem of finding the Hamiltonian isotopy classes of monotone tori in S^2xS^2.