VictorJuiz/thesis huggingface dataset:
The Rational Design and Synthesis of Graphene Nanoribbons and Graphene Nanoribbon Functional Nanoarchitectures

Graphene nanoribbons (GNRs) are narrow strips of graphene that have exceptional phys-ical and electronic properties. GNR band-gap engineering by ﬁne-tuning the width, edge geometry, and doping pattern of GNRs is required for integration into post-silicon electronic devices. To this end, we have developed several techniques to create armchair and chevron GNRs of varying widths (Chapter 2). In order to further tune the electronic properties of GNRs, we explore the synthesis and applications of a series of doped GNRs (Chapter 3). Namely, incorporating N-, O-, and S-dopant atoms along the edges of chevron GNRs induces a characteristic shift in the energy of conduction and valence band edge states. Furthermore, the controlled synthesis of atomically-precise bottom-up GNR heterojunctions represents a critical step toward the goal of integrating GNRs into device applications where their ex-ceptional electronic properties can be exploited. To this end, we developed two methods of creating atomically precise GNR heterojunctions (Chapter 4), ﬁrst via post-synthetic mod-iﬁcation of the GNR edges, and second by employing a hierarchical growth process. Our work demonstrates tunable methods for band-gap engineering of graphene nanostructures for advanced electronic applications.

Advisor: Fischer, Felix R
Investigating Dysregulated Metabolic Pathways that Drive Cancer Pathogenicity

In the United States, it is estimated that over 200,000 women will be diagnosed with/nbreast cancer and nearly 40,000 women will die of breast cancer in 20161. Mortality/nfrom breast cancer is almost always attributed to metastatic spread of the disease to/nother organs, thus precluding resection as a treatment method.2 Unfortunately,/nconventional chemotherapy fails to eradicate many aggressive breast cancers. Studies/nover the past decade have uncovered certain breast cancer cell-types, such as/nestrogen/progesterone/human epidermal growth factor receptor 2 (ER/PR/ HER2)-/nnegative (triple-negative) breast cancers (TNBCs) that show poor prognosis and/nchemotherapy resistance within breast tumors.3–5 Eliminating these breast cancer types/nis critical in reducing the mortality associated with breast cancer. Current therapeutic/nstrategies for breast cancer include resection, nonspecific therapies such as radiation or/nchemotherapy, and targeted strategies for combating certain types of breast cancers./nHowever, there are no targeted strategies for combating the most aggressive types of/nbreast cancers, including TNBCs./nCancer cells are known to possess altered metabolism that fuels their malignancy and/npathogenicity. Most of what has been known about cancer cell metabolism focuses on/nthe well-characterized central carbon pathways, however, the mapping of the human/ngenome revealed that cellular metabolic networks extend far beyond that. In this/ndissertation I present some extensions of our understanding of dysregulated cancer cell/nmetabolism in areas of lipid metabolism and membrane glycosylation. Furthermore,/nusing drugs and drug candidates already in clinical trials or the clinic, I identify new/nmetabolic targets that, when inhibited, contribute to or are responsible for killing TNBC/ncells. Increasing our understanding of cancer cell metabolism, especially in the context/nof small molecule inhibitors, will hopefully enable or promote the development of/ntargeted therapeutics for these highly lethal and poorly treated cancers.

Advisor: Nomura, Daniel K
System Architecture and Signal Processing Techniques for Massive Multi-user Antenna Arrays

Future advancements in wireless communication standards will rely on two inter-related technologies. First, to address the saturation of traditional cellular spectrum in the $<6$ GHz bands, new and much-higher frequency mm-wave spectrum will be utilized. The mm-wave bands at 24, 28, 39, 60, and 72 GHz, among others, have tens of gigahertz of available and unused spectrum. Second, because modern coding and modulation techniques make near-optimal use of time and frequency resources, the spatial dimension of wireless channels must be exploited to send data streams in a spatially selective manner only to the desired users./nFrom an engineering perspective, both of these technology trends rely on the design of antenna arrays --- spatial selectivity is achieved by having a large number of radios while mm-wave operation needs directional transmissions to overcome the propagation loss. Designing large antenna arrays --- on the order of 64-256 or larger number of radios --- represents a huge departure from traditional radios used in wireless networks which have at most 4 independent radiators and transceiver chains./nThis thesis explores system architecture, signal processing, and hardware design techniques which are suitable for massive antenna arrays which form many spatial beams simultaneously. First, beamforming is identified as the preferred spatial processing technique for the large array regime, and a beamforming-aware array architecture is proposed which is modular, scalable, and distributed. The core element of the proposed array architecture is a common module which integrates multiple transceivers, analog and digital signal processing, and interconnect. Additionally, a time-domain beamforming algorithm is proposed for channels with strong multipath components./nNext, synchronization architectures and algorithms are proposed for both carrier and baseband synchronization in massive antenna arrays. It is shown that uncorrelated phase noise between different transceivers causes decoherence between the front ends. Accordingly, a synchronization strategy consisting of co-optimized carrier recovery loops and distributed phase-locked loops (PLLs) is proposed to manage the total phase noise impact in antenna arrays. For baseband synchronization, a hierarchical timing alignment strategy is proposed which uses a background calibration loop to compensate for front-end and sampling skews while using distributed data timing recovery to compensate for true time delay effects in large arrays./nFinally, hardware implementations of these system- and signal-processing-level ideas are demonstrated. The first prototype consists of a system-on-chip for low-frequency massive MIMO. The proposed SoC integrates multiple full digital radios with on-chip DSP and serial links. The second prototype demonstrates the first massive, multi-user phased array operating at 72GHz. A 128-element phased array is implemented using off-the-shelf components which can form 16 simultaneous beams over 250MHz bandwidth, for an aggregate capacity of 20 Gbps.

Advisor: Nikolic, Borivoje
Designing a Scalable and Affordable Fluoride Removal (SAFR) Process for Groundwater Remediation in India

Globally, 200 million people are at risk of adverse health effects from drinking groundwater contaminated with geogenic fluoride concentrations exceeding the World Health Organization’s maximum contaminant limit (WHO-MCL = 1.5 mg F−/L). Although many defluoridation technologies have been demonstrated to work in lab, most have proven inappropriate for developing countries because they are cost-prohibitive, require skilled labor, or are difficult to scale. Activated alumina (AA) column filters are widely used by the upper middle class but production of AA remains costly in terms of money, energy, and greenhouse gas emissions. Eliminating these energy-intensive steps in refining bauxite, a ubiquitous aluminum-rich ore ($30/tonne), to AA ($1500/tonne), has the potential to reduce the annual per-capita material cost of treated water significantly./nThe purpose of this dissertation is to ascertain the use of bauxite as a potentially inexpensive defluoridation technology through experimental studies characterizing globally diverse bauxite ores and tradeoffs associated with mild processing steps to enhance fluoride removal performance. Chapter 1 presents an overview of fluoride as a geogenic groundwater contaminant worldwide and in India, the health effects of excess fluoride consumption, and existing treatment technologies. Chapter 2 establishes proof of concept that mildly processed bauxite can effectively remediate field-relevant fluoride concentrations to below the WHO-MCL in synthetic and real groundwater matrices at comparable kinetics and significantly lower cost than AA. This chapter also characterizes intrinsic features of globally diverse bauxite ores (from Guinea, Ghana, USA, and India) to identify factors predicting bauxite’s performance. Chapter 3 utilizes insights on underlying molecular mechanisms and proposes thermal activation and groundwater pH adjustment as two processing methods to optimize the fluoride removal performance of bauxite. Chapter 4 discusses some remaining practical challenges and unknowns for implementing our scalable and affordable fluoride removal (SAFR) process in the field. Chapter 5 concludes this dissertation by discussing the implications of the research findings and by suggesting additional future studies needed before field implementation of the proposed SAFR groundwater treatment technology.

Advisor: Gadgil, Ashok J
Effects of County Strategies to Scale Evidence-Informed Social Services

A persistent and seemingly intractable problem is the systemic failure to successfully scale evidence-informed social services to a level that achieves population-level improvements in well-being. There is a growing call for governments to enter the scaling environment as primary coordinators, trainers, and funders. Prior scholarship has identified four strategies governments may employ to enact these roles: convene and support high-level leadership teams, assess organizational readiness, provide technical assistance, and align funding. But it is unclear whether use of any or all of these government scaling strategies is sufficient to achieve desired outcomes. Moreover, prior scholarship largely focused on state and federal government roles, largely ignoring how these factors might operate in local government environments. Yet counties may hold the greatest scaling leverage because they often have well-established relationships with service providers through shared clients, contracts, and advocacy. The current study, thus, aimed to provide much needed insight into the relationship between these strategies and scaling outcomes in a local governmental context. Drawing data from a single county with a stated goal of scaling evidence-informed practices across human service organizations, it used public government records and crowd-sourced and computational data-extraction methods to create measures of these four alternative strategies. It assessed the relative effects of these strategies on scaling progress using time-to-event analysis. It found that county governments are well positioned to implement scaling strategies and that the proportion of social service providers adopting evidence-informed services can increase, as can the proportion of county funding directed to these organizations. It also found some empirical support for a link between three of the strategies and scaled evidence-informed services—convening a leadership team, assessing readiness, and aligning funding. Moreover, it identified a new and potentially desirable county strategy—establishing a shared local measure of evidence-informed service. This study design is highly replicable and as such provides a general model to apply to other local environments to identify common county levers that effectively promote the scaling of evidence-informed social services.

Advisor: Stone, Susan I
Structure and Mechanism of the Formylglycine-generating Enzyme

The ability of enzymes to make rapid the conversion between chemical entities represents an enabling feature for life. The strategies by which enzymes achieve this feat are manifold in their details and physiological consequences. Though the central importance of biological catalysis has been known for well over a century, the true breadth of enzyme function is still beginning to be appreciated. A fundamental description of enzyme catalysis is essential to understanding biological processes, and is also necessary in order to realize the promise of engineered enzymes for transforming medicine and manufacturing./nThe formylglycine-generating enzyme (FGE) is responsible for activating sulfatase enzymes in aerobic organisms by catalyzing the post-translational modification of a cysteine residue to formylglycine. Formylglycine permits sulfatase activity by acting as a covalent cofactor. Thus, the diverse roles of sulfatases in both animal and microbial biology underscore the importance of FGE. However, early investigations made clear that this enzyme operates by a novel mechanism with a unique protein fold. In turn, elucidation of the details of this biochemical transformation have remained enigmatic for almost two decades./nThis dissertation describes the structural and biochemical interrogation of FGE in pursuit of understanding its catalytic mechanism. Chapter 1 places into context the physiological importance and biochemical curiosities of formylglycine and FGE. In Chapter 2, I present the first structural and spectroscopic characterization of copper-bound FGE, defining it as a novel enzyme with intriguing features related to function. Finally, Chapter 3 reveals detailed structural and kinetic proof for several critical steps of catalysis by FGE, allowing the formulation of a mechanistic framework for further investigation.

Advisor: Bertozzi, Carolyn R
Klinman, Judith P
Threat modeling and circumvention of Internet censorship

Research on Internet censorship is hampered by poor models of censor behavior. Censor models guide the development of circumvention systems, so it is important to get them right. A censor model should be understood not just as a set of capabilities—such as the ability to monitor network traffic—but as a set of priorities constrained by resource limitations./nMy research addresses the twin themes of modeling and circumvention. With a grounding in empirical research, I build up an abstract model of the circumvention problem and examine how to adapt it to concrete censorship challenges. I describe the results of experiments on censors that probe their strengths and weaknesses; specifically, on the subject of active probing to discover proxy servers, and on delays in their reaction to changes in circumvention. I present two circumvention designs: domain fronting, which derives its resistance to blocking from the censor's reluctance to block other useful services; and Snowflake, based on quickly changing peer-to-peer proxy servers. I hope to change the perception that the circumvention problem is a cat-and-mouse game that affords only incremental and temporary advancements. Rather, let us state the assumptions about censor behavior atop which we build circumvention designs, and let those assumptions be based on an informed understanding of censor behavior.

Advisor: Tygar, Justin D
Gamma-Ray Observations of Solar Flares with RHESSI Imaging Spectroscopy and the GRIPS instrument

Solar flares can release ~1e33 ergs of power, accelerate particles to relativistic speeds, heat plasma to ~15 million K and catastrophically reorganize 1e5 km long field structures in 100s - 1000s of seconds. Magnetic reconnection of large-scale field structures in the corona are thought to power flares, but the precise mechanisms that convert the stored magnetic energy into particle kinetic energy are poorly understood./nFlare spectra in the 20 keV - 10 MeV energy range are rich with information that provide a window into the underlying physics of flare particle acceleration. This hard X-ray (HXR)/gamma-ray emission can be used to understand electron and ion dynamics, particle abundances and the ambient plasma conditions in solar flares. Enhanced imaging, spectroscopy and polarimetry of flare emissions in this energy range are needed to address the current era of particle acceleration and transport questions, including: What causes the spatial separation between HXR emission generated by relativistic electrons and the gamma-ray line emission from energetic ions? How anisotropic are the relativistic electrons, and why can they dominate in the corona? How do the compositions of accelerated and ambient material vary with space and time, and why?/nThe Reuven Ramaty High Energy Solar Spectroscopic Imager (RHESSI) instrument, launched in 2002, provided the first combined imaging and high-resolution spectroscopy in the HXR/gamma-ray range. RHESSI's volumes of detailed study on electron-associated emission <1 MeV is in contrast to comparatively few ion-associated gamma-ray observations. Over the past two solar cycles RHESSI has imaged only five flares at the 2.2 MeV neutron-capture line and has been able to resolve ion lines in ~30 events. My research aims to expand this small set gamma-ray flare observations by (1) using new techniques to study flares obscured by high-background counts in the existing RHESSI dataset and (2) providing new observations through the development and flight of the Gamma-Ray Imager/Polarimeter for Solar Flares (GRIPS) instrument.

Advisor: Boggs, Steven
Inventory Models Motivated by Biopharmaceutical Manufacturing

The biopharmaceutical industry now is entering a more mature stage of its existence. In order to prepare for increasingly fierce competition, firms are beginning to shift their focus from developing new technology to improving manufacturing operations. However, the nature of biomanufacturing poses many unique challenges for the industry. In this thesis, we consider three closely related inventory models to address the challenges these firms are facing./nIn the first model, we consider an inventory planning model with batch differentiation. Batch production is a natural constraint in biomanufacturing and the decision of how many batches to produce and how to differentiate the batches is crucial. In this work, we propose a series of heuristic algorithms using the idea of certainty equivalent control which converts a difficult stochastic integer programing to a deterministic problem. We show that our heuristic algorithms perform extremely well when the demand variation is small and we also explore how the trade-off between demand information and decision dynamics affects the performance./n/nIn the second model we combine the inventory model with a queuing model to address the tactical level supply chain management and coordination issue between the manufacturer and a third party contractor. Small biopharma firms usually outsource the filling/labeling/packing operations to a third party contractor. As a consequence, the firm experiences large uncertainty in the time until the outsourced order is returned. We show that a capacity reservation contract that places an order at fixed intervals with a capacity constraint can outperform the traditional inventory management $(r,q)$ policy by not only reducing the inventory cost at the firm, but also increasing the total profit of the entire system./n/nIn the third model, we extend the traditional process flexibility literature by integrating inventory capabilities and give general guidelines on how to design an effective supply chain network. Given the expensive inventory storage capability in the biopharmaceutical industry, firms are often interested in incorporating flexible plants that can produce multiple types of product into an existing dedicated supply chain to better respond to demand uncertainty. We develop models that help the firm explore many important strategic issues, such as whether a new plant should be flexible or not, and whether and which plants should be modified to have inventory capabilities.

Advisor: Kaminsky, Philip
Everything old is new again: robust predictive frameworks for shifting host-pathogen interactions in the face of global change

Disease ecology urgently requires powerful predictive tools that anticipate the links between global change and emerging infectious disease. However, the ecological context of emerging disease remains poorly understood, especially given that the majority of parasites in any given ecosystem have no direct impact on human health. This dissertation explores a global change biology approach to host-pathogen interactions, focused on understanding both positive and negative impacts of climate change on parasites and pathogens. Chapter 1 reviews current theory surrounding extinction, including mathematical modeling approaches at scales from population extirpation up through global extinction rates. Community-level approaches to extinction risk estimation are applied in Chapter 2, which includes forecasts for climate-driven range shifts based on the largest macroparasite occurrence dataset yet assembled. Up to a third of parasites could face extinction in a changing climate, especially accounting for co-extinction with hosts. However, we find no evidence that wildlife parasites face better or worse odds of survival (or have different hotspots of diversity) based on their potential to infect humans. The results of this study indicate the hundreds of thousands, or potentially millions, of parasitic species on Earth are likely to be redistributed around the globe in a hard to predict pattern, with unknown effects on wildlife and human health. The same species distribution modeling methods from Chapter 2 are used in Chapter 3 to predict the global distribution of Zika virus, an emerging infection from 2016 with a still largely unresolved eco-epidemiology. The conflict among different models and modeling approaches surrounding Zika's distribution is considered in Chapter 4, by interfacing these models with simulations of potential epidemics in the United States. Overall, this dissertation addresses the idea that in the face of global change, ecologists will play an increasingly important role in predicting shifting landscapes of disease. However, the overwhelming focus on emergence ignores the importance of extinction as a potentially complementary phenomenon within ecosystems; and the varied approaches within ecology, and the short timescale on which ecologists work during current outbreaks, pose a disciplinary problem with no clear answer.

Advisor: Getz, Wayne M