VictorJuiz/thesis huggingface dataset:
Machine learning assisted biomedical diagnosis and chemical optimizations
Keywords: Chemistry.

This thesis focuses on applying machine learning methods on the process of biomedical diagnosis and chemical optimizations. The first part describes the combinination of ambient ionization mass spectrometry and machine learning for non-invasive biomedical diagnosis. In this design, mass spectrometry is used to collect chemical information from a biological sample; while machine learning methods are employed to give predictions based on the information. Moreover, the important chemicals in the prediction process can be pin-pointed by feature selection algorithms. Those chemical structures are further identified by tandem mass spectrometry. The second part of this thesis concerns solving chemical optimization problems with reinforcement learning. The processes of optimizing the yield of a chemical reaction and the property of a molecule are formulated as Markov decision processes, and solved by different reinforcement learning algorithms.
Machine learning for a sustainable world
Keywords: Electrical Engineering.

In 2015, the United Nations General Assembly set 17 Sustainable Development Goals to serve as the guiding principles for international development over the next 15 years. This thesis explores how machine learning could help to address some of these global sustainability challenges. The first part of the thesis focuses on data gaps in the developing world that make it hard to measure progress and target intervention effectively. Traditional data collection methods like household surveys are slow and expensive. Combining machine learning with passively collected remote sensing data could prove to be a scalable alternative, but a lack of labeled data poses a major challenge for sustainability applications. To combat this data scarcity, we propose a transfer learning approach that uses nighttime lights as a proxy for economic development. By extracting predictive features from daytime satellite imagery, we can generate fine-grained poverty and wealth estimates and create high-resolution maps of poverty. Next, we present semi-supervised deep kernel learning (SSDKL) to leverage the large amounts of unlabeled satellite data. We demonstrate that SSDKL learns more generalizable features and improves performance on a range of semi-supervised regression tasks. Finally, we introduce Tile2Vec, an unsupervised representation learning algorithm. We evaluate Tile2Vec on a wide range of remote sensing datasets, and show that it even works on non-image spatial data. The second part of the thesis explores culture-free diagnostics for bacterial infections, a leading cause of death in developing nations. Current diagnostic methods require sample culturing to identify the bacteria and its antibiotic susceptibility, a slow process that can take days even in state-of-the-art labs. Broad spectrum antibiotics are often prescribed while waiting for culture results, leading to suboptimal therapy and contributing to the increased prevalence of antibiotic resistance. We present a proof-of-concept system that combines Raman spectroscopy and deep learning to achieve accurate bacterial identification and susceptibility testing in a single step. We generate an extensive dataset of bacterial Raman spectra, and show that we can accurately identify 30 common bacterial pathogens. Even on low signal-to-noise spectra, we achieve antibiotic treatment identification accuracies of 97% and distinguish between methicillin-resistant and -susceptible isolates of Staphylococcus aureus (MRSA and MSSA) with 89% accuracy. Finally, we validate our results on clinical samples spanning 50 patients, where we achieve treatment identification accuracies of 99.7%.
Market Concentration, Earnings and Turnover: No-Poaching Clauses in the Quick Service Restaurant Industry
Keywords: Department of Economics
No-Poaching Clauses
Market Concentration
Quick Service Restaurant
Franchisor
Turnover
Earnings
Herfindahl-Hirschman Index
Group-Specific Labor Index
United States
Thesis

I analyze the impact of Quick Service Restaurant franchisors’ no-poaching clauses on historical employee earnings and turnover for the Restaurants and Other Eating Places industry. I examine the 41 largest Quick Service Restaurant franchisors and the labor markets of 10 major U.S. cities over 11 years from 2006 to 2016. No-poaching clauses restrict intra-franchisor movement of employees and, if in use, can be found in a brand’s franchise disclosure documents. I create a panel dataset using no-poaching agreements data, industry data on earnings and turnover, and business establishments’ employment data. Using a panel regression with fixed city and time effects, I determine that no-poaching clauses have an insignificant effect on turnover but do exhibit a statistically significant effect on earnings. Specifically, a 25 percent increase in market concentration related to no-poaching agreements results in a 2-6 percent decrease in average monthly earnings, depending on employment status, age, and education level.
Market Timing: A Myth or a Possibility? Individual Investor and Mutual Fund Performance in the Stock Market
Keywords: Economics
finance
investing
stock market
Federal Reserve
mutual fund
Thesis

Investors are always looking for ways to increase their portfolio returns, ideally without taking on additional risk. Some investors pay others to manage their money, while other investors turn to market timing strategies, believing they can pick individual stocks or funds that will do better than a market benchmark. However, the current literature is divided on whether these market timing strategies are effective in reality. This paper analyzes a new market timing strategy for individual investors that uses changes to the Federal Funds rate target to indicate market entry and exit. The results of this analysis show that individuals cannot use these simple signals in order to consistently achieve higher portfolio returns than market benchmarks. This paper also analyzes allocation and return data for a new set of actively managed mutual funds. The results from these correlative analyses suggest that mutual funds also do not have positive market timing ability even though they have more capital and resources. Overall, this paper supports research claiming that investors, whether as individuals or as part of a fund, do not have the ability to consistently time the market and achieve significant and positive returns above market benchmarks.
Markets, Money and Might: Chinese Economic Statecraft and a Case Study of the 21st Century Maritime Silk Road Initiative
Keywords:  Stanford Global Studies
Stanford Global Studies
East Asian Studies
Chinese foreign policy
Chinese law
Belt and Road Initiative
state-business relations
port governance
Thesis

Economic statecraft is a state’s deliberate manipulation of economic interaction or deployment of economic resources to defend its national interests and further its strategic goals. The practice of economic statecraft on a globally significant scale is changing both the nature of diplomacy and the logic and operation of markets. Some contend that the introduction of geopolitical logic into commercial deals render once-distinct security and economic considerations harder to disentangle, raising the risk that disagreements in one field can trigger a reaction in another. China has often been described as the world’s leading practitioner in geoeconomics. The increasing and diversified incidences of the use of economic statecraft as China’s tool of influence in the game of international politics, coupled with the lack of clarity and underlying mistrust regarding the current and future intentions and capabilities of this rising power, have prompted allegations that these less conventional shows of national strength are aimed at potentially upending the extant international order and have stoked concerns that these acts could undermine the laws and norms governing the conduct of international relations. Some of these allegations and concerns are legitimate, some misguided, and others overdrawn. It is, therefore, the modest aim of this thesis to lend some perspective to these concerns. With a view to analytically separate speculation from substance, this thesis assesses several of these claims in the specific context of the 21st Century Maritime Silk Road or Maritime Silk Road Initiative (“MSRI”). As one of China’s foremost displays of economic statecraft, the MSRI provides an important empirical arena in which to observe the interplay between strategic and economic considerations, and serves as a bellwether for the successes and limits of the tools of economic statecraft.
Matching in online market platforms
Keywords: Management Science and Engineering.

The thesis contains three parts which provide for an in depth study of problems that are motivated from challenges faced by online platforms. The first two parts study matching problems in decentralized and centralized environments respectively and the third part is concerned with the aggregation of preferences. The first part of the thesis considers the problem of assortment planning in two-sided platforms, where self-interested agents are present on each side of the platform. While assortment planning has been studied extensively in the revenue management literature, it is concerned with the problem of assigning menus of goods (as opposed to people who can reject) to agents. In our problem, agents' utilities are derived from a random utility choice model (RUM). Two different design settings are explored - simultaneous (both sides propose at the same time) and sequential (one side proposes first). The optimal menu is completely characterized for the case of a single customer where a greedy algorithm is shown be optimal. Both design settings turn out to be NP-Hard for multiple customers. Two heuristics are proposed and a constant factor approximation algorithm is provided for the sequential setting. The second part of the thesis considers a centralized marketplace, where agents (drivers and passengers) arrive in an online manner and are matched after a possible delay. Agents arrive at a given set of locations which form a metric (distance between points satisfying the triangle inequality) and the platform needs to minimize the sum of distance and waiting costs. A natural trade-off that arises is the following: matching agents faster reduces waiting costs but waiting for more agents to arrive allows to create better matches. A randomized and a deterministic algorithm are proposed on the tree metric (that has been embedded from the original metric); both of which achieve a constant competitive ratio on the tree metric leading to a logarithmic competitive ratio on the general metric. The third part of the thesis looks at pairwise comparisons among agents specifically in the context of intransitivity. The goal is to develop and analyze parametric models that can support intransitivity. The key result is that such models have non-concave likelihood functions. Next, taking inspiration from the Condorcet paradox, a majority vote model is proposed. The majority vote model can support strong and arbitrarily long intransitive cycles and shows comparable performance against other parametric models which support intransitivity on publicly available datasets.
Mathematical and physical space in Kantian idealism
Keywords: Philosophy.

Kant's transcendental idealism aims to explain how we have mathematical knowledge. It frames space and time as pure 'forms' of our ability to acquire sensations, rather than as independently existing entities or their properties. This is then also supposed to explain how we can anticipate formal features of experience. The space we study in geometry is the very one in which objects appear to us. In the last several decades, however, scholarship has implicitly recognized Kant's notion of space is not as unified as this picture would suggest. In particular, the straightforward assumption that there is just one space - both mathematical and physical - has implicitly come under scrutiny. I locate grounds for this scrutiny within Kant's direct and indirect proofs for transcendental idealism. However, I argue the disunity of space actually strengthens Kant's doctrine. I clarify how Kant intends to incorporate Newtonian matter theory while responding to Leibnizian rationalism. To do this, I specify the evidential hurdles Newton faced in determining whether gravity is a well-founded physical magnitude. I suggest Kant's evolving criticisms of physical monadology gradually include more of Newton's matter theory. The inclusions reflect Kant's growing clarity on his precise disagreements with Leibniz. The core of these, I argue, is the distinction between matter and form as it applies to thought.
Measurement and control of non-adiabatic dynamics a study in the acetylene dication
Keywords: Physics.

Non-adiabatic structural dynamics occur in lighter molecules and are often described using Conical Intersections (CI) in molecules with at least three atoms. Light that is resonant near regions of strong non-adiabatic coupling can play an important role in controlling and understanding these dynamics. This thesis presents both simple model simulations and experimental data in the acetylene dication to analyze how light interacts with non-adiabatic dynamics. A key parameter that relates how the nuclear energy changes in time compared to the relative electronic energy is used to explain and predict the role that dipole coupling has in controlling non-adiabatic dynamics.
Measurement and maintenance of human cell size
Keywords: Biology.

How cells reach and maintain the right size is a longstanding question in biology. Moreover, the many ways in which cell size may influence cellular physiology have received insufficient attention. Research has been hindered by inadequate tools for measuring size in living cells. In this dissertation, a novel strategy is developed to measure the size of single human cells using a nuclear-localized fluorescent protein expressed from a constitutive promoter. This method is validated by comparing it to established alternatives, with the result that the fluorescence measurements are more robust and less dependent on image segmentation than the commonly-used measurement of nuclear volume. Then, this strategy is applied to understand the size dependence of a crucial part of the cell cycle -- the transition from G1 to S phase -- and how it contributes to cell size homeostasis. One hypothesis is that titration of a size-proportional factor against a size-independent molecular factor could function as a "molecular ruler" to create a size-dependent biochemical signal. Several cell cycle regulatory proteins are tested as candidates and it is observed that one of them, the retinoblastoma protein Rb, is unique in its size-nonscaling behavior: Rb is diluted during G1 phase. This property of Rb is a consequence of its synthesis, partitioning, and degradation pattern. Finally, it is demonstrated that Rb concentration is a size-dependent determinant of cell cycle progression. Future areas of inquiry include the phenomenology of cell growth, mechanisms of size scaling, and in vivo size homeostasis.
Measurements with optically levitated microspheres
Keywords: Physics.

I discuss the development of optically levitated microspheres as a tool for precision measurements and tests of fundamental physics. Micron-scale dielectric spheres are trapped by the radiation pressure at the focus of a Gaussian laser beam, where the optical suspension enables thermal, electrical, and mechanical isolation from the surrounding environment at high vacuum. Forces and torques can be measured from changes in the angle and polarization of light both transmitted through and reflected by the trapped particle. Additionally, the charge of the particle can be controlled with single electron precision. We have used these methods for the following three purposes: to search for fractionally charged particles and dark energy, to develop measurement techniques for surface potentials, and to construct an electrically driven micro-gyroscope.
Measuring, mitigating, and modeling the impact of skin treatments and solar exposure on the barrier function of human stratum corneum
Keywords: Materials Science and Engineering.

The biomechanical behavior of human stratum corneum (SC), the outermost layer of skin, is critical for its large role in providing the barrier function of human skin. The degradation of the SC's natural biomechanical function can thus lead to painful skin conditions such as atopic dermatitis, exacerbated wounds and scarring, and reduced compatibility of wearable electronic devices. However, the effects of synergistic environmental exposures and most topical cosmetic treatments on key mechanical properties such as stress and intercellular cohesion in the SC have not been previously quantified and their mechanisms of action remain poorly understood. Consequently, the first step necessary to make informed designs of protective or stress mitigating treatments is to elucidate the underlying mechanism in the SC of mechanical stress, the driving force for damage to the skin barrier function. As a result, the critical connection between water volume loss during drying and stress development is introduced. The effect of treatment molecules, such as emollients and moisturizers, on macroscopic stress and cohesion is then analyzed through the presented framework, thus significantly clarifying the treatment characteristics necessary to mitigate SC damage. After establishing the role of treatments to protect the skin, the impact of simultaneous ultraviolet (UV) light and heat exposure (to approximate infrared radiation) is quantified to demonstrate the ability of synergistic solar damage processes in the SC to enhance stress and reduce intercellular cohesion, thus increasing the risk of barrier function degradation. In this context, the efficacies of UVB absorbing molecules (and their carrier vehicle) to protect the SC biomechanical properties from UV damage is investigated. This results in a new understanding of multiple mechanisms (i.e. water loss, treatment molecule diffusion, environmental damage, photoabsorber protection) that may simultaneously affect SC biomechanics, a vital step towards the successful protection and maintenance of a healthy skin barrier function.
Measuring political connections in Brazil
Keywords:  Department of Economics
Department of Economics
Brazil
political connections
campaign finance
Thesis

This paper investigates the returns of contributions to electoral campaigns on the market value of firms. The hypothesis is that contributing to a federal representative or senator leads to higher stock returns for the firms that made these contributions. I implement an event study strategy using data from the Supreme Electoral Court on campaign contributions and from the São Paulo Stock Exchange on historical prices to test my hypothesis. I find some evidence that firms that contribute to campaign winners have returns higher than one would expect right after the election. The intensity of this impact seems to be influenced by how much a firm contributed to campaign winners and by how many campaign winners a firm contributed to.
Mechanism of non-neuronal fate repression during C. elegans neurogenesis
Keywords: Biochemistry.

Cellular differentiation is defined by tuning of the cell's transcriptional program into its target. Examples of developmental repressors such as REST suggest that non-target programs need to be repressed in parallel to activating the target programs. While it is well established that proneural genes activate neuronal transcription programs, little is known about how differentiating neurons repress non-neuronal programs to ensure neuronal fates. Myt1 family factors are transcriptional repressors that contribute to neuronal reprogramming from non-neuronal cells in vitro, but their function during neuronal differentiation remain unclear. In this dissertation, I characterize the sole C. elegans Myt1 family ortholog ZTF-11. We show that ZTF-11 is required for neurogenesis in multiple neuronal lineages from previously differentiated epithelial cells, including a neuron generated from a developmental neuronal transdifferentiation event. ZTF-11 is exclusively expressed in all neuronal precursors with remarkable specificity at single cell resolution, likely through direct activation by proneural genes. ZTF-11 is required to eliminate epithelial identity from neurons generated from epithelial precursors. In these neurons, loss of ztf-11 results in loss of neuronal identity. Ectopic expression of ZTF-11 is sufficient to generate additional neurons through repressing epithelial identity. In contrast, neurons generated from dedicated neuronal lineages are still generated without ZTF-11, suggesting that neurons face different developmental challenges from non-neuronal programs. Loss of ztf-11 results in upregulation of many non-neuronal genes. ZTF-11 functions together with MuvB corepressor complex to repress its target genes. These results provides insights on the ability of Myt1l to drive neuronal transdifferentiation in vitro as well as the developmental role of Myt1 family factors. Taken together, I identify an evolutionarily conserved mechanism to specify neuronal fates by repressing non-neuronal genes.
Mechanisms and kinetics of silicon under dynamic compression
Keywords: Mechanical Engineering.

This thesis analyzes the dynamic material response of crystalline silicon to laser-driven shock loading. As a shockwave passes through the silicon, it generates a high-pressure, high-temperature environment that causes the material lattice to compress, deform, adopt new high-pressure phases, and eventually enter a melt state. Measuring these responses utilizes an ultra-bright, ultrafast x-ray source capable of capturing the lattice and atomic motions in-situ. The first experiment (Chapter 3) characterizes the loading source, a high-power optical laser at the Matter in Extreme Conditions endstation of the Linac Coherent Light Source. Analysis of the drive system optimized the experimental setup to send steady-pressure, spatially-uniform shockwaves through the silicon. The second experiment (Chapter 4) builds on the results of the first experiment, driving high-pressure (> 20 GPa) shocks through pure crystalline silicon samples. Using a setup configuration that places the x-rays transverse to the optical drive laser beam, this experiment takes simultaneous, ultrafast x-ray diffraction and direct x-ray imaging data of the lattice response. A series of focused spatial and temporal scans determines the kinetics of the elastic, inelastic, and melt waves. Additionally, wide field-of-view x-ray imaging spatially resolves these responses and illuminates an intermediate elastic wave. The third experiment (Chapter 5) analyzes additional data to extract the density of the imaged silicon melt in-situ, a long-standing challenge in the dynamic compression community. It establishes a positive trend between drive pressure and melt density while simultaneously quantifying the change in transformed material volume. A final experiment (Appendix B) examines the photon flux on-target in the Matter in Extreme Conditions endstation. It determines the effect of beamline configuration on the delivered number of x-rays - a critical value for expanding the results of this thesis to new low-transparency and/or high-Z materials.