VictorJuiz/thesis huggingface dataset:
Towards a regional and urban air mobility future : the development of computational approaches for quantifying trade-offs in electric aircraft design

Air travel is rapidly changing before our very eyes. From the multitude of ways in which we perceive sustainability to our evolving perspectives on connectivity, transportation by air has once again become a topic of earnest discussion. Once theorized and in some cases attempted modes of air travel that have long been considered impractical or unachievable have again resurfaced to garner substantial attention within industry, government and academia. The focus of this work is one of these modes of air travel - the movement of people, goods and services between confined spaces in densely populated areas. Coined regional and urban air mobility (RUAM), this mode of transportation has reignited the idea of using both short and vertical takeoff and landing aircraft that offer advantages in both speed and range compared to personal automobiles, rideshare services and other forms of public ground transportation. Furthermore, these aircraft can potentially facilitate other niche applications such as air ambulances, search and rescue missions, surveillance and commercial cargo delivery. However, despite recent technological advances providing the impetus for realizing RUAM, several questions pertaining to vehicle design, electrification, infrastructure, regulations, and societal constraints remain unanswered. Making inroads into some of these impeding challenges, this dissertation seeks to streamline the understanding of critical aspects of the design process for these aircraft via three key milestones. The first of which is the adoption of computational techniques capable of providing fast and accurate predictions of both physical components as well as the whole aircraft. The second is the representation of realistic flight dynamics for these non-conventional aircraft. Lastly, the third is the use of flight profiles that symbolize realistic routes through urban canyons. Specifically, within this work, the two critical aspects of aircraft noise and propulsive efficiency are positioned under the microscope whereby the nuances of their relationship that manifest at the system-level are identified and explored

Keywords: Aeronautics and Astronautics.
Advisor: Alonso Juan José
Kroo Ilan
Lele Sanjiva K. (Sanjiva Keshava)
Towards accessible quantum chemistry and automated photochemical design via machine learning and nonadiabatic dynamics simulation

The ability to reliably design molecular systems for targeted applications has the potential to revolutionize drug and material discovery. Quantum chemistry can now accurately predict useful chemical properties for a wide range of molecules and continues to enhance its predictive power as new algorithms and hardware come online. However, several major hurdles remain. In this work, I focus on two outstanding challenges: building accessible tools for the wider chemistry community to interact with quantum chemistry, and designing photochemical systems with nonadiabatic dynamics simulations. I develop ChemPix, a hand-drawn hydrocarbon structure recognition software to provide an almost barrierless molecule input method for computational chemistry software. ChemPix and other accessible molecular input tools are combined with cloud-based GPU- accelerated quantum chemistry and extended reality visualization to build a series of interactive quantum chemistry tools. These tools can compute quantum mechanical properties in real-time from hand-drawn structures or voice input. Photochemical systems can be modeled with nonadiabatic dynamics simulations. However, the complex multi-reference electronic structure calculations required for these simulations means that modelling even simple photochemical processes demands domain expertise and substantial human effort. Here, I employ cis-stilbene, a prototypical photo- switch, to explore the path towards automated photochemical design. First, nonadiabatic dynamics simulations of cis-stilbene are performed and analyzed to uncover the cis-trans photoisomerization and photocyclization mechanisms. Next, I propose the use of ensembled simulations to build stronger mechanistic predictors and link the predictions to the experimental ultrafast electron diffraction signal. Finally, a highly symmetric light- induced molecular motor is designed based on the simulations by photo-exciting cis- stilbene with circularly polarized light

Keywords: Chemistry.
Advisor: Martinez Todd J. (Todd Joseph)
Markland Thomas E.
Rotskoff Grant
Towards an Equitable Development of the Regional Earthquake Resilience of the Greater Metro Manila Area, Philippines

The Philippines with its densely populated Greater Metro Manila Area faces serious threats to the security of its people, livelihood, and infrastructure from unpredictable earthquakes due to its proximity to the Pacific Ring of Fire. For the past decades, the country’s earthquake resilience has been centered solely on the structural health of a single building without any extensive reference to the socio-economic capacity of its community. Previous large-scale earthquake risk studies also focused only on the well-known “Big One” magnitude-7.2 earthquake scenario for post-earthquake response planning purposes and neglected the probabilistic behavior of earthquake occurrence that can be a basis for policies that could mitigate the risk to the communities. Using the recently released probabilistic earthquake hazard maps in 2020, this study performed the first metropolitan-scale estimation of average annualized earthquake economic losses and ratios of 23 municipalities and cities in the Greater Metro Manila Area and compared the findings with the current socio-economic productivity parameter called the 2021 Cities and Municipalities Competitive Index developed by the national government. Our findings revealed a prevailing disconnect between the socio-economic capacity of different local jurisdictions and their degree of earthquake risk of economic losses, casualties, and damaged floor areas. Our study presents different policy recommendations that can be implemented at the regional and local levels toward an equitable development of earthquake resilience in the region.

Keywords: Public Policy Program
Baker, Jack
Earthquake Risk
Regional Resilience
Metro Manila
Philippines
Stanford University
Humanities and Sciences
Public Policy Program
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Thesis
Towards characterizing the distinct contributions of genetically defined neuron populations in value-based decision making

Animals must constantly engage in economic choice behaviors, evaluating the available options in their environments and deciding which to pursue. However, how these decisions are computed in the brain remains poorly understood. One reason for this is because most studies of this form of decision-making have been performed in primates, for which we currently lack tools for recording and manipulating the activity of defined cell types. Here, in preliminary work I analyze single cell activity data from mice and reveal differential responses to cue and reward in excitatory and inhibitory populations of neurons. This highlights the need for the development of economic choice paradigms that can be integrated with animal models and tools for the manipulation of genetically defined cell types. To meet this need, my honors thesis implements a head-fixed, value-based decision-making paradigm in mice. Using the behavioral apparatus and training protocol designed, mice learned to choose between two olfactory cues that predicted the delivery of one of the two reward types (sugar water or water). Analysis of choice data reveals that mice make appropriate decisions based on reward type and amount, suggesting they integrate information about both reward quality and quantity to guide behavior. With this paradigm in mice, we will be able to exploit the genetic accessibility of the mouse to probe neural circuits that mediate economic decisions.

Keywords: Bioengineering
Choice (Psychology)
Neurosciences
Calcium imaging
Neural circuitry
Choice (Psychology) > Economic aspects
Reward (Psychology)
Substance abuse
Drug addiction
Decision making > Psychological aspects
Bioengineering
Orbitofrontal Cortex
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Thesis
Advisor: Deisseroth Karl
Gore Felicity
Boahen Kwabena
Towards controlling active matter : from light control to topological traps

Activity can organize matter in unique configurations inaccessible to equilibrium systems. The potential to harness principles of self-organization by studying active matter has immense implications in engineering and design. In the first part of this dissertation, I propose a self-driven microfluidic device propelled by a suspension of active, light-controllable molecular motors. Surface-driven flows are ubiquitous in nature, from subcellular cytoplasmic streaming to organ-scale ciliary arrays. We model how confined geometries can be used to engineer complex hydrodynamic patterns driven by activity prescribed solely on the boundary. Specifically, we simulate light-controlled surface-driven flows, probing the emergent properties of a suspension of active colloids that can bind and unbind from surfaces of a closed microchamber, together creating an active carpet. The attached colloids generate large scale flows that in turn can advect detached particles towards the walls. Switching the particle velocities with light, we program the active suspension and demonstrate a rich design space of flow patterns characterised by topological defects. We derive the possible mode structures and use this theory to optimize different microfluidic functions including hydrodynamic compartmentalisation and chaotic mixing. Our results pave the way towards designing and controlling surface-driven active fluids. In the second part of this disseration, I shift gears and discuss a structure formed by the collective motion of a species of gliding, filamentous cyanobacteria we term the "active spiral". How persistent yet dynamic patterns can form in motile active systems remains an open question. We leverage the ability to segment and track each filament individually to gain insight into this question, giving us single-particle resolution into the spiral dynamics. Due to the reversible gliding motility of individual filaments in the spiral, the filaments shear past each other with no coherent system-level vorticity, forming highly dynamic structures exhibiting radial material flux. These rearrangements are primarily driven by rules of interaction between motile tips. We enumerate these rules of interaction on a polar coordinate lattice, and show we can predict material flux within the system as a result. We also present the discovery of a new topological trap in active spirals, which creates un-crossable boundaries in an otherwise dynamic structure capable of material movement. Interestingly, these topological traps arise purely from the geometry of long filaments with winding number greater than zero. Understanding the dynamics of an active system with single filament resolution enables the detailed understanding of particle interactions, a necessary step toward controlling active matter

Keywords: Applied Physics.
Advisor: Bryant Zev David
Prakash Manu
Spakowitz Andrew James
Greenleaf William James
Towards equity in algorithmic decision making

In recent years, many high-stakes societal decision-making systems have begun incorporating data and algorithms. This trend raises the question of how decision makers can do so in a way which creates equitable systems which ameliorate inequities. This dissertation considers two broad paths forward towards this goal. First, we review a series of interventions at various stages of the model-building and deployment process. Specifically, we consider how a model-builder might selectively acquire additional information, adaptively sample training data, and add personalization. We show that these interventions allow for model-builders to efficiently allocate resources to create decision-making systems which are inclusive of individuals from vulnerable groups. Second, we review two pieces of work where modern, online data sources give insights which can inform improvements for existing systems. In particular, we first consider how telematics data, containing records on the true prevalence of speeding, sheds light on inequities in traffic enforcement. Then, we see how online game records provide valuable insight into how users make decisions within social networks. Findings from both studies can be incorporated in future design of or interventions in decision-making systems within both spaces. Overall, this dissertation demonstrates two concrete paths for moving towards equitable decision making: intervening to efficiently improve outcomes for underserved groups, and leveraging insights from modern data sources to improve societal decision making systems

Keywords: Management Science and Engineering.
Advisor: Goel Sharad
Ugander Johan
Ashlagi Itai
Towards irregular computation on regular dataflow

This thesis presents my work on expanding the bounds of programmability for vectorized reconfigurable dataflow accelerators (vRDAs). vRDAs, including Plasticine and the SambaNova RDU, promise users more eﬀicient computation by eliminating the overheads of modern von Neumann machines—instruction fetch, dynamic scheduling, speculation, and caching. Instead of fetching instructions from a cache and data from a register file and then executing code in a single physical location, vRDAs lay out computation across an entire chip. Each instruction is mapped to a pipeline stage, and data flows through those stages. Similarly, instead of coordinating memory transfers through a cache hierarchy (with the overhead of prefetching and reordering), vRDAs use explicitly coordinated scratchpads to provide low-overhead, high-throughput on-chip accesses. However, to practically use a vRDA, applications must be compiled from a high-level language, and previously only dense linear algebra could be compiled to Plasticine using the MapReduce programming model as implemented in Spatial. This programming model limited applications to counter-based iteration with aﬀine memory accesses and prevented control flow within the innermost parallel region. I overcome these limitations via Capstan and Revet. First, Capstan uses new hardware to introduce support for direct iteration on a variety of sparse tensor formats, including sparse-dense and sparse-sparse iteration. Then, Revet builds on Capstan and Aurochs to support inner-loop control flow by compiling an imperative language to dataflow using a streaming, embedded-control tensor format. For vRDAs, Capstan and Revet both provide zero-to-one improvements: they enable applications that could not previously be mapped. They are 4.3x smaller than an Nvidia V100 GPU, 17x faster for sparse applications, and 3.8x faster for applications with inner-loop control flow

Keywords: Electrical Engineering.
Advisor: Olukotun Oyekunle Ayinde
Kjoelstad Fredrik
Raina Priyanka (Assistant Professor of Electrical Engineering)
Tracking charge migration with attosecond X-ray pulses from a free-electron laser

The motion of electrons in molecular superposition states happens on the attosecond timescale, roughly three orders of magnitude faster than nuclear motion. To study the first steps in a photochemical reaction, then, we must study the electron dynamics in early times before the nuclei have a chance to move. These purely electronic dynamics, uncoupled from nuclear motion, are dubbed charge migration (CM). CM can be described as a coherent superposition of delocalized electronic states evolving in time, which appears as a time-dependent oscillation in charge density across the molecule. On longer timescales, thought to be tens of femtoseconds, nuclear motion couples to the pure electronic CM. This tends to average out the CM, and there is evidence that this process can influence the nuclear reaction pathways. One can further envision using sequences of laser pulses to prepare CM states as a method of coherent control directing photochemical reaction pathways. However, understanding the loss of electronic coherence as nuclear motion occurs is difficult. Theoretical modeling of CM is computationally challenging, and there are open questions about the effects of nuclear motion. Experimental measurements can guide us towards better, more efficient approximations to help answer these outstanding questions. To this end, I present two experiments towards developing two separate methods for measuring CM. Both methods rely on the recently developed attosecond X-ray free-electron laser source at the LCLS free-electron laser facility. These two methods for measuring CM serve as early implementations of this new attosecond X-ray source. The first method to study CM, impulsive ionization, prepares a CM state by ionizing with an attosecond X-ray pulse which has coherent bandwidth large enough to populate multiple cationic states. The final state is then measured with X-ray absorption spectroscopy. I present preliminary results showing signatures of CM and nuclear motion damping the time-dependent charge density. The second method, nonlinear X-ray spectroscopy, is a sophisticated toolset using sequences of X-ray pulses to prepare and measure CM states. I present a measurement of a basic building block of nonlinear X-ray spectroscopy, impulsive stimulated X-ray Raman scattering, and use this result to show the feasibility in the near future of measuring valence CM states in a neutral molecule

Keywords: Physics.
Advisor: Bucksbaum Philip H.
Cryan James
Marinelli Agostino
Reis David A.
Transcriptomic analysis of Ustilago maydis infection and improving cassava brown streak disease surveillance in sub-Saharan Africa

Ustilago maydis is a smut fungus that is distinctive for its ability to infect and form tumors in all aerial organs of corn. Previous research has shown that different sets of fungal effector genes are expressed depending on the tissue and cell type being infected although there is limited information on how the gene expression changes over the course of the infection, particularly in anthers. In this thesis I study early infection of maize tassels using both whole tissue and single cell RNAseq. Problems with being able to select infected tissue and the sc-RNAseq sequencing depth, severely limited the conclusions I was able to draw, and I propose potential improvements for subsequent studies on cell type specific plant infection. Cassava brown streak disease (CBSD) is a looming threat to food security for small holder farmers as it rapidly spread across sub-Saharan Africa. Currently, many countries across sub-Saharan Africa conduct annual surveys on the prevalence of CBSD, and a range of management interventions have been proposed to minimize yield loss in regions where CBSD has become endemic. In this thesis, I developed two stochastic epidemiological models for the spread of CBSD with a field and for conducting country wide surveys that I used to compare the efficacy of different interventions and survey protocols. At the scale of a individual farmer's field, I find that introduction of virus-free 'clean seed' effectively increases yield across a wide range of disease pressures. I evaluated the effectiveness of the current survey protocol at detecting the presence of CBSD within a field, and found that it is relatively effective at low levels of CBSD prevalence and that the probability of detection can be meaningfully increased by surveying later within the growing season, particularly in areas with high vector density. I then extended the field level model to simulate the effectiveness of different protocols for conducting annual country level surveys for CBSD by combining it with a second model of landscape level CBSD spread. I find that with the current protocol, detection of newly infected districts is limited by the small number of infected fields surveyed. Changing the current protocol of uniformly allocating surveys across Nigeria to surveying locations proportional to the density of cassava greatly improves the effectiveness of CBSD detection, and to a lesser extent so does increasing the annual number of surveys conducted. This effect is consistent across multiple districts in Nigeria and multiple ways of quantifying survey efficacy. Finally, with these simulation results I also propose guidelines for practical, actionable recommendations for the deployment of management strategies and survey protocol modifications in sub-Saharan Africa

Keywords: Bioengineering.
Advisor: Walbot Virginia
Bergmann Dominique
Fischbach Michael
Long Sharon R.
Transformers, Humans in Disguise: Applying NLP Based Computational Techniques to Deliberative Democracy

This project seeks to apply a scalable, NLP based computational mechanism to automate portions of the work done by the Center for Deliberative Democracy (CDD) in their Deliberative Polling project. The machine based classifier that this project is attempting to profile is intended to emulate the currently manual task of tagging transcripts of worldwide deliberations about controversial topics with the intention of 1. Extracting argument dialogue segments and 2. Assessing argument deliberative quality as per the conventions set forth by the CDD. Top level, these techniques involve humans tagging transcripts using a 0, 1, 2, 2+ scale, reflecting the respective number of provided reasons to support an argument. The computational techniques that will be profiled for their capacity to replicate human tagging that this project will explore will be transformer based language models such as XLNet, a custom bag of words (BOW) + random-forest based classifier, and random chance. Empirical results have displayed an increase in model generalizability when transferring to the XLNet model, indicating a better capacity to emulate human transcript tagging across all categorizations, conversational subjects, and discussion locales.

Keywords: Deliberative democracy
Natural language processing (Computer science)
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Thesis
TRAPing Context- and Region-Specific Ensemble Activity Induced by (±) 3,4- Methylenedioxymethamphetamine

(±)3,4-Methylenedioxymethamphetamine (MDMA) has gained considerable traction as a novel therapeutic avenue for treatment-resistant psychiatric illness. Prior research suggests MDMA exerts its prosocial therapeutic effects via discrete nuclei in the striatum. Yet, the anatomical and functional features of these neuronal populations remain unclear. Using transgenic mice enabling activity-dependent neuronal labeling, we examine the region- and context-specific characteristics of neuronal ensembles generated following systemic MDMA delivery. This approach reveals MDMA-induced ensembles in unique segments of the nucleus accumbens (NAc) alongside the extended dorsal endopiriform cortex and claustrum (DEn/Cl). Ensembles in the NAc lateral shell are comparable following drug administration in social or nonsocial environments. By contrast, ensemble densities in the NAc medial shell and DEn/Cl are more robust when MDMA is delivered in social versus nonsocial conditions. This effect is replicated by d-fenfluramine (FEN), a selective serotonin-releasing compound. In describing the anatomical and context-dependent features of distinct MDMA ensembles, we set the foundation for broader functional studies.

Keywords:  Department of Biology
MDMA, fenfluramine, methamphetamine, TRAP, neurobiology, biology, psychiatry
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Thesis
Advisor: Heifets Boris
Malenka Robert
Chen Xiaoke