VictorJuiz/thesis huggingface dataset:
Management of digital transformation projects in the AEC industry
Keywords: Engineering.

The rise of digitalization over the last couple of decades has opened new avenues for the Architecture, Engineering, and Construction (AEC) industry in terms of value creation. This immense potential of digitalization has motivated numerous AEC companies to invest in developing and adapting their digital capabilities. However, despite this enthusiasm, 85% of current big data and digitalization projects fail to deliver the anticipated value and many AEC companies are becoming increasingly anxious about their technology investments. They are struggling to reconcile their traditional and digital perspectives and are uncertain about prioritizing technology investments or selecting from competing technologies when developing digital strategies. Based on our interactions with over 200 practitioners, we observed that a part of this problem arises from two primary factors: (1) Inability to define (and therefore select) what "digitalization" means in a specific use case, given that there is little that cannot be digitalized, and (2) A lack of understanding of how to strategically implement the chosen form of "digitalization" and which stakeholders to involve in the process. To address this gap, this research makes four contributions. These findings are based on the data collected over five years (2018 -- 2023) from three primary sources: (1) Sixteen real-world longitudinal cases spanning between three to eighteen months, (2) Workshops with 173 executives involved in 53 digitalization projects across 42 companies, and (3) Interviews with over 30 experts, involving more than 70 hours of interaction. First, this research proposes a two-dimensional Levels of Digital Twin framework. This framework organizes the types and levels of digitalization according to their unique features and advantages. Furthermore, it highlights the efforts required to build these digitalization levels. Second, this work contributes the Digitalization framework. This framework helps practitioners select the suitable level of digitalization for their specific use case, thus building on the previously defined Levels of Digital Twin. Third, this study proposes a taxonomy for the common starting points for digitalization efforts in the AEC industry. This taxonomy helps practitioners assess their starting point before implementing the selected level of digitalization and determine the most appropriate implementation strategy. Fourth, this research contributes a 3-by-3 digitalization management framework. This framework outlines the strategic processes to follow and the stakeholders to involve in digitalization projects for a successful implementation. The validation of the frameworks revealed that practitioners found them useful in practice to better plan and develop digital strategies. However, the generalizability of the frameworks is limited, given that the case studies are only from the engineering and construction industry. Future research could focus on comparing the findings and their implications with the challenges facing manufacturing, software, and service companies.
Manipulating space and time in visual media
Keywords: Engineering.

With the increased usage of digital technology, visual media has become a popular form of communication and is widely used for storytelling and art. Often times, authors of visual media may wish to make spatial or temporal edits in post-production. However, it can be difficult to author edits while preserving realism. One main issue is that there are many constraints involved in realism, which limit the edits that can be achieved given user-specified inputs. Moreover, often times these constraints are not explicitly defined. In this work, we introduce task-dependent realism, which explicitly defines realism for a target manipulation task. We focus on two manipulation tasks and identify spatial and temporal properties to relax to achieve a greater number of realistic-looking edits. This thesis contributes: 1) spatial and temporal constraints to relax and maintain for two manipulation tasks, based on perceptual properties; and 2) techniques which automatically maintain and relax these constraints as the user specifies input constraints and explores edits.
Manipulation and reasoning methods for embodied object search
Keywords: Engineering.

Embodied agents often need to find objects to achieve downstream tasks, which makes it valuable to study solutions to the challenges posed by embodied object search. These challenges will depend on the environment the agent needs to search in: in small environments such as a bin or a shelf the primary challenges will relate to manipulation in clutter and perception in the presence occlusions, whereas in larger environments such as a room or an apartment the agent will also have to reason about where objects are likely to be and navigate to these locations. In this talk, I will present new methods for solving this variety of challenges -- with a focus on manipulation and reasoning -- in a variety of environments, and with a variety of techniques. Specifically, I will present formulations of the problem in the context of seeking to extract an object from a bin, to reveal a hidden object on a tabletop, to predict an object's location in a house, and to remember patterns of object movement in a variety of households. For each formulation, I will present a novel learning-based approach that expands on or pushes beyond what was achieved previously. These approaches will involve object segmentation, object recognition, grasp planning, teacher-aided reinforcement learning, procedural environment generation, graph neural networks, and more. I will conclude by discussing how these methods can be refined and combined to enable embodied agents to find objects in novel real world environments
Manvising in the U.S. : how some men advise and women's perceptions of their status
Keywords: Humanities and Sciences.
Psychology.

In U.S. popular culture, some women report that men "manvise" or give them unsolicited, generic, and prescriptive advice. Six studies (N = 4,102) investigate the impact of this type of paternalistic advice on women's status perceptions. Chapter 1 introduces the problem of "manvising" and Chapter 2 confirms that women perceive that men more often give unsolicited, generic, and prescriptive advice than women do. Chapter 3 uses vignette studies to show that men manvising leads women to anticipate having less status themselves and that women in general will have less status in the future. These effects were somewhat attenuated when men provided more responsive advice, and were mediated by perceptions of responsiveness, or the extent to which people feel understood and validated. Chapter 3 also explored the unique effects of men manvising: women anticipated feeling greater gender identity threat when men (vs. women) give unsolicited, generic and prescriptive advice. Chapter 4 examines manvising during live text interactions and shows that women felt less respected when partnered with men who manvised. In contrast, when partnered with men who asked more questions, women reported feeling greater state status. Furthermore, Chapter 4 also finds that men perceive having a larger self and feel more heard when they manvise. Overall, this initial examination of the phenomenon of manvising suggests that it is an everyday conversational practice that may subtly reduce women's perception of their status and also reinforce their perceptions of the gender hierarchy, which may in turn contribute to women's lower status and gender inequality in the U.S.
The many roles of protein methylation in MRna translation and human cancer biology
Keywords: Humanities and Sciences.
Biology.

The human genes eEF1A and eEF2 encode essential enzymes that facilitate one of the most fundamental processes in biology: mRNA translation elongation. Both eEF1A and eEF2 are targets of lysine methylation. The lysine methyltransferase (KMT) enzymes that target eEF1A and eEF2 are commonly associated with human cancers. Given the possibility that these methylation events contribute to human disease, it's imperative to determine what their molecular functions are. The work described in this dissertation partially characterizes the biological functions of eEF1A and eEF2 methylation in mRNA translation and cancer. Further, this work leverages a new artificial intelligence technology, AlphaFold, to characterize the physical FAM86A-eEF2 interaction, advancing the possibility of developing a highly specific FAM86A inhibitor for therapeutic use.
Many-body spin physics with quantum gases in a confocal cavity
Keywords: Humanities and Sciences.
Physics.

Ultracold gases confined inside optical cavities enjoy photon-mediated interactions enhanced by the cavity's cooperativity and have brought on new paradigms in many-body physics. Carefully engineered light-mediated interactions between multilevel atoms can render this a study of spin physics. In this dissertation I describe the realization of various exotic many-body spin phases in a cavity apparatus that can be tuned between a traditional single-mode configuration and multimode confocal geometry. I will demonstrate the realization of a spin-textured checkerboard, along with a checkerboard with dislocation. Then, the cavity is used to realize dynamical spin-orbit coupling. Finally, I demonstrate the realization of a novel, fully-connected, vector spin glass unique to the confocal cavity.
Mapping cellular and molecular programs for ultra-rapid alveolar epithelial regeneration
Keywords: Medicine.

With each breath gasses are exchanged across extraordinarily thin and expansive alveolar type I (AT1) cells adapted for diffusion. Cuboidal alveolar type II (AT2) cells are interspersed and act as stem cells. Even transient disruption of this delicate monolayer epithelium can result in capillary leak and respiratory failure. Here, we exploited genetic and chemical methods to ablate AT1 cells and dissected the earliest steps in alveolar regeneration. This uncovered ultra-rapid AT2-to-AT1 cell transdifferentiation that enabled near-continuous maintenance of the epithelial barrier. Proliferation subsequently restored AT2 cells in two phases, immediate mitosis of binucleated AT2 cells followed by replication of mononucleated AT2 cells. EGFR regulated both M phase entry of binucleated cells and S phase entry of mononucleated cells in a Wnt-dependent manner. Repeated cycles of AT1 cell death did not compromise the barrier, but rather elicited epithelial hyperplasia that fortified the epithelium during ongoing injury then spontaneously resolved. We propose a two-step mechanism in which regeneration of the epithelial barrier precedes stem cell proliferation
Mapping the neural dynamics of locomotion across the Drosophila brain
Keywords: Medicine.

In this thesis, I develop a method to measure neural activity across the entire brain of the fruit fly Drosophila melanogaster while the animal walks. I create a standard anatomical atlas of the in vivo fly brain, the Functional Drosophila Atlas (FDA), and build a pipeline to accurately register volumetric imaging data from individual animal brains into this common space with micron precision (Chapter 2). I then analyze this dataset to reveal the brain-wide spatiotemporal dynamics associated with locomotion and describe several key findings (Chapter 3). We find that locomotor-related information is indeed widespread across the brain, extending well beyond classical motor-associated regions. We observe remarkable topographic structure within many individual brain regions, with neurons preferring specific behavioral features grouped together. We find that as the animal modulates its forward or rotational velocity, the neural activity evolves across the brain in distinct patterns. Activity in some brain regions precedes behavior by 300 milliseconds, is contemporaneous in others, and lags behind behavior by many seconds in others. As neural activity sweeps across the brain, it sequentially engages clusters of neurons with different behavioral specificities, suggesting a spatiotemporal framework for the emergence of complex walking maneuvers. By registering this data into FDA we gain access to connectomics resources, which we apply to identify candidate neurons involved in modulating the forward or rotational velocity of the animal. Finally, we address the question of volition, or how the brain might plan future behavior in the absence of sensory cues (Chapter 4). We highlight that when performing a turn, the brain experiences a widespread asymmetry in neural activity across the two hemispheres. Strikingly, this asymmetry emerges more than 10 seconds before the turn in a small sub-compartment of a motor-associated region, the Inferior Posterior Slope (IPS). The difference in neural activity in this region across the two hemispheres can predict the direction of future turns on a trial-by-trial basis, and ultimately provides an opportunity for dissecting a neural circuit involved in volitional action.
Mapping the therapeutic checkpoints of the STING pathway
Keywords: Humanities and Sciences.
Chemistry.

The cGAMP-STING pathway is crucial for the activation of the innate immune system against cancer. This thesis contributes to understanding the regulation of cGAMP in two ways. First, existing tools to quantify cGAMP fall short of scientific needs, particularly in terms of accessibility and throughput. The development of cGAMP-Luc, a high-throughput, sensitive and precise enzymatic assay for the quantitation of cGAMP in complex biological samples bridges this gap. cGAMP-Luc enables the characterization of transporters of cGAMP as well as novel inhibitors of cGAMP hydrolases. Second, the hydrolases of cGAMP are important targets for inhibition in the treatment of cancer. Through studies of ENPP1-/- mice, this thesis explores the existence of cGAMP hydrolases and their physiological relevance in cancer
Market design for non-profit applications
Keywords: Engineering.
Management Science and Engineering.

This dissertation is a collection of three essays, each studying a market design setting where the exchange of money is not allowed. There are many real world markets where the exchange of money is considered either legally or ethically unacceptable, such the allocation of school seats, donor organs, or subsidized housing. For these kinds of markets, the market designer must use other strategies to influence the behavior of the participants and affect the outcomes of the market. Each of the three chapters analyzes how the rules of a given kind of market will affect the welfare of the participants along dimensions such as efficiency, fairness and diversity. Chapters one and two study theoretical models, the first is a model of one-sided assignment where a set of items is being allocated to a set of participants, and the second is a model of two-sided matching where doctors and hospitals first interview to learn more about their preferences before being matched. Chapter three describes an applied project where we leveraged the theoretical and empirical literature on school choice to help redesign the student assignment policy in the San Francisco Unified School district (SFUSD)
MCMC with substitutions and multi-armed bandits with covariates : theory and applications
Keywords: Engineering.

The first part introduces a new approach to nonparametric multi-armed bandit theory involving both the bandit and the covariate processes. The extension to bandit processes with a non-denumerable set of arms is also discussed. The approach developed herein can be readily extended to continuous-time processes by using arm elimination. It also carries out a stochastic search for a nearly optimal arm at covariate values in a given set before applying arm elimination. The procedure is shown to attain the asymptotically minimal rates for the regret over the given set. The second part discusses a new adaptive MCMC algorithm where acceptance rates are significantly improved. The basic idea is to approximate a target distribution by the empirical distribution of representative atoms, chosen sequentially by an MCMC scheme so that the distribution converges weakly to the target distribution as the number of iterations goes to infinity. We also establish the asymptotic normality of the Monte Carlo estimate of a functional of the target distribution and provide a consistent estimator of its standard error. The third part builds a data-driven methodology for the performance reliability and the improvement of sensor algorithms for automated driving perception tasks. The methodology takes as input three elements: one or various algorithms for object detection when the input is an image, a dataset of camera images that represents a sample from an environment, and a simple policy that serves as a proxy for a task such as driving assistance. We develop a statistical estimator, which combines these elements and a data augmentation technique, in order to rank the reliability of perception algorithms which is measured as the chance of collision given the speed of the ego vehicle and the distance to the closest object in range
Measurement of electric quadrupole and magnetic octupole susceptibilities of certain cubic praseodymium-containing compounds
Keywords: Humanities and Sciences.
Physics.

Susceptibility, original developed experimentally in the context of magnetic systems, is here applied to the magnetic octupole and two-dimensional electric quadrupole. PrV2Al20 and PrTi2Al20 are motivated as model systems, realizations of electric quadrupole and magnetic octupole order without significant competing lower-order multipolar order (such as magnetic order). Basic methods to probe the susceptibilities are then discussed, with emphasis on the careful use of properties of cubic symmetry to isolate the desired multipolar moments. A variety of experimental methods to probe the octupolar susceptibility are outlined, using combinations of strain and magnetic field to induce an octupolar moment. Limitations and advantages of each are noted. The AC elastocaloric effect, wherein oscillating strain is used to induce temperature oscillations in a material based on the entropy landscape thereof, is then motivated as a particularly powerful tool for probing the octupolar susceptibility. Experimental data using this technique on PrV2Al20, a system with realized magnetic octupolar order, is presented and analyzed, with a temperature-derivative of the octupolar susceptibility extracted. Lastly, the unique symmetry properties of the two-dimensional electric quadrupole and their implications are discussed in depth. Data is presented using the elastocaloric effect to probe the associated susceptibility in PrTi2Al20. The efficacy of the techniques used, and limitations thereof, are then discussed, along with potential means of improvement. Further potential applications of the techniques herein developed are briefly noted
Measuring and teaching problem-solving practices in digital learning environments
Keywords: Education.

Digital learning environments are becoming increasingly ubiquitous as a wide range of EdTech products and services enter classrooms and households across the globe. One salient attribute of these environments is their capacity to generate large amounts of data as students interact with the technology. These data logs can help construct a detailed picture of how students work on a task and provide valuable insights into their underlying competencies. At the same time, the sheer volume of interaction data poses challenges, such as how to extract meaningful behavioral patterns from the raw data and model them to assess specific constructs. This dissertation contributes to the efforts of educational researchers and practitioners in harnessing the data generated by digital technology to support teaching and learning, with an emphasis on using interactive tasks to assess and teach problem-solving practices
Measuring and understanding interactions across temporal and spatial scales in multicellular tissues
Keywords: Engineering.
Bioengineering.

This thesis includes work in two distinct yet connected areas, focusing on biological interactions across temporal and spatial scales in multicellular tissues. First, I develop a method to improve the resolution and capture efficiency of spatial transcriptomics. Second, I combine approaches of molecular and cellular studies with physical modeling to investigate systemic wound responses during whole-body regeneration in planarian. In the first part, we significantly improve the performance of capture array-based spatial transcriptomics, which is commonly used to analyze gene expression in diverse tissue contexts. Its spatial resolution is currently limited by the density of the barcoded arrays. To overcome this, we introduce Expansion spatial transcriptomics (Ex-ST), a method that involves clearing and expanding the tissue before capturing the entire polyadenylated transcriptome using an enhanced protocol. This approach allows us to achieve higher spatial resolution and capture efficiency which we demonstrate using mouse brain samples. In the second part, we examine the distant responses induced by injury, the functions and mechanisms of which remain largely unknown. Using planarian flatworms capable of whole-body regeneration, we report that injury induces Erk activity wave to travel at a speed 10-100 times faster than those in other multicellular tissues. This ultrafast propagation requires longitudinal body-wall muscles, elongated cells forming dense parallel tracks running the length of the organism. The morphological properties of muscles allow them to act as superhighways for propagating and disseminating wound signals. Inhibiting Erk propagation prevents tissues distant to the wound from responding and blocks regeneration, which can be rescued by a second injury to distal tissues shortly after the first injury. Our findings provide a mechanism for long-range signal propagation in large complex tissues to coordinate responses across cell types and highlight the function of feedback between spatially separated tissues during whole-body regeneration.
Measuring cross-sectional variation in expected returns : a machine learning approach
Keywords: Business.

I develop and test a new machine learning method for estimating cross-sectional firm-level expected returns. My approach adapts the loss function of a random forest algorithm to minimize the variance of measurement errors instead of trading off bias and variance. Out-of-sample tests show this approach yields reliably higher cross-sectional accuracy relative to: (a) commonly used implied cost of capital estimates, (b) factor-based estimates, and (c) estimates based on other state-of-the-art machine learning algorithms. In more detailed analyses, I find that while a small number of firm characteristics explain most of the returns predictability, the relative importance of these characteristics vary by holding horizon. Further, cross-sectional differences in expected returns exhibit limited persistence beyond two years. I also use this new approach to revisit the reported association between earnings smoothness and expected returns. Contrary to prior studies, I show that firms whose earnings are smoother relative to their cash flows earn higher (not lower) expected returns, despite being safer on many dimensions