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“We’ve Got a 4/20 in Progress”: Effects of Dallas Cannabis Policy on Police Productivity
No full textThe war on drugs widened the scope of the criminal justice system, increasing the frequency of
police contact and collateral consequences for people who use drugs. Proponents of cannabis
policy reform argue that, in addition to correcting these consequences, decriminalizing cannabis
will enhance productivity and resource allocation for police departments. However, there is little
research that explores the validity of this argument. The aim of this dissertation is to examine the
impact of three cannabis decriminalization policies on measures of police productivity. Data
from 2014-2021 were collected from the Dallas Police Department’s Open Data Portal (cannabis
arrests), Records Management System (RMS) (case processing times), and Computer Aided
Dispatch (CAD) (response times). Multi-group, single intervention interrupted time series
analyses (ITSA) were estimated to investigate whether enacting decriminalization policies led to
increased police productivity. Preliminary results indicate that processing times for cannabis
cases significantly increased following enactment of each policy. This study has potential
implications for law enforcement practices, filling a gap in the research on how decriminalization
can affect police practices, and offers areas for reform
Investigating the Role of Patterned Tissue Stiffness, Cell Proliferation and YAP Localization in Embryonic Kidney Development
No full textDuring renal development, the metanephric kidney arises when the ureteric bud forms along the
Wolffian duct and undergoes a series of branching events to build the ureteric tree. The tips of this
tree interact with renal vesicles in the metanephric mesenchyme to induce the formation of
developing nephrons and later fuse with them to form the filtration system within the kidney.
Kidney development, is an understandably a complex process, regulated in parts by GDNF/Ret
and Wnt signaling. A well-formed network of collecting ducts is essential for normal kidney
functioning as defects in branching morphogenesis are thought to be associated with chronic
kidney diseases. Proper renal branching morphogenesis depends crucially on cell proliferation,
and it is observed that proliferation is elevated specifically at the tips of branching ureteric tree.
Whether or not proliferation is developmentally patterned within the developing kidney and what
regulates this pattern of proliferation, is poorly understood. Although tissue mechanics has been
shown to influence the morphogenesis of other branched organs, such as the lung and mammary
gland, it is unclear how biophysical factors within the embryonic kidney, such as tissue stiffness
and cell proliferation, affect renal development and, how changes in the mechanical environment
in the embryonic kidney might interact with signaling cascades, such as the Hippo pathway, or
those downstream of GDNF, Wnt, and TGF-β, which are known regulate renal branching
morphogenesis. In this work, we quantified regional differences in tissue stiffness within the
embryonic kidney and investigated how these variations influence the patterns of proliferation that
sculpt the ureteric tree. We also investigated the effect on branching morphogenesis when patterns
of proliferation and Yap localization were disrupted. Taken together our data will help elucidate
the role and regulation of patterned biophysical factors within the embryonic kidney and its effect
on branching morphogenesis. These findings will further our understanding of branching-related
kidney diseases and can provide better insight towards tissue engineering efforts of rebuilding a
kidney
Data-enhanced Stochastic Dynamical Modeling for Wind Farms
No full textLow-fidelity analytical models of turbine wakes have traditionally been used to demonstrate
the utility of advanced control algorithms in increasing the annual energy production of
wind farms. In practice, however, it remains challenging to achieve significant performance
improvements using closed-loop strategies that are based on conventional low-fidelity models.
This is due to the over-simplified static nature of wake predictions from models that are
agnostic to the complex aerodynamic interactions among turbines. In this thesis, we offer a
stochastic dynamical modeling framework to improve the predictive capability of low-fidelity
models while remaining amenable to control design. The framework is capable of capturing
the effect of atmospheric turbulence on the thrust force and power generation as determined
by the actuator disk concept. In this approach, we use stochastically forced linear models of
the turbulent velocity field to augment the analytically computed wake velocity and achieve
consistency with higher-fidelity models in capturing power and thrust force measurements.
The power-spectral densities of our stochastic models are identified via convex optimization
to ensure statistical consistency while preserving model parsimony. We demonstrate the
utility of our approach in estimating the thrust force and power signals generated by large-
eddy simulations of the flow over a cascade of turbines. We also evaluate the capability of
our models in predicting turbulence intensities at the hub height of a multi-turbine wind
farm
Paths to Non-ergodic Quantum Dynamics: From Cavity QED to Strong Zero Modes
No full textRecent advances in cold atoms experiments and the development of superconducting circuits have revolutionized the way we can examine, observe and implement new physical
phenomena. In such systems, we can realize new classes of quantum systems which exhibit
non-equilibrium quantum phenomena. These systems have attracted mcuh attention in
the past two decades as they possess new physics absent in equilibrium. Beside interesting rich physics to learn more about quantum systems, understanding non-equilibrium
systems are crucial in developing future technologies such as quantum computation and
communication.
Given that many open questions needed to be answered in the study of non-equilibrium
quantum systems, in this dissertation we will present our theoretical and numerical attempts in providing answers to some of these questions. One of the key features of the
non-equilibrium system is how the dynamical properties of quantum systems cane be
characterized in different conditions. Here we will present our result on two different
mechanism a system can avoid ergodicity.
Many-body localization (MBL) is an extension of Anderson localization to interacting systems, where adding strong enough disorder (breaking translational symmetry by adding
random potential such as impurity in crystals) can impede the conductivity (system
becomes insulator) in the quantum system. Most of the known MBL systems are short-
range interacting particles, but in this dissertation, we will discuss MBL in the presence
of coupling of the matter to cavity/circuit QED mode where the combined system becomes long-range interacting. We will study the two cases of weak coupling and strong
coupling regimes and will derive the effective Hamiltonian using the high-frequency expansion for each case of coupling strength. We predict that the cavity QED has new
localization behaviors such as an inversion of the mobility edge where the high-energy
states are localized and low-energy states are delocalized. Also in the strong coupling
limit, we observed that using the idea from coherent destruction of coupling the system
can show signs of localization for photon number as low as n ∼ 2.
The rest of this dissertation is devoted to understanding how a clean system (no disorder)
can possess symmetry-breaking edge modes indefinitely, or for a long enough but finite
time. The case with infinite lifetime edge mode is called strong mode (SM) and the
case with finite lifetime edge mode is known as almost strong mode (ASM). Our system
of interest is a clock Z3 model which is an extension of the Ising Z2 models. In the
clock model (Baxter and modified Baxter) we found that the chirality of the interaction
is essential in deriving the exact edge mode in the Hermitian model but removing the
hermiticity (controlled by a parameter β), the effect of chirality on the stability of the edge
mode becomes less important. We attempt to use different numerical and approximation
techniques such as Krylov Hamiltonian and dynamical signature to characterize the edge
mode in a Z3 model
Off the Platter and Out of the Kitchen: Food Things in American Fiction, 1860 - 1945
No full textTo the detriment of various academic studies, scholars habitually overlook foods that appear in
literature outside of traditional settings of dining room platters and kitchen pantries or that
remain unconsumed. I utilize thing theory to identify the foods’ common characteristics and
patterns, unconsumed foods appearing in non-traditional settings, and define them as ‘food
things.’ The resultant interpretations of food things broaden the perspective of social norms
regarding food and culture. Studying food things addresses neglected areas of scholarly research;
namely, (1) thing theorists do not study food objects, and (2) social sciences do not utilize fiction
works as primary historical sources. Studying foods through thing theory also creates an avenue
for unorthodox comparisons of fiction works and their authors. This dissertation identifies a
pattern of food things in select American fiction from 1860 to 1945. The analysis is in three
parts: (1) women’s fiction of the late nineteenth and early twentieth centuries; (2) men’s war
literature from the late nineteenth to mid-twentieth centuries; and (3) immigrant fiction from the
early twentieth century.
I discuss works by Louisa May Alcott, Kate Chopin, Willa Cather, Stephen Crane, Ernest
Hemingway, Norman Mailer, Anzia Yezierska, Ole Edvart Rölvaag, and Pietro di Donato. The
work of thing theorists Bill Brown, Barbara Johnson, and Elaine Freedgood inform my approach,
illuminating how food functions as material objects in literature. A composite analysis pinpoints
the intersection of history and the food's human-object interactions through close reading of the
text, culinary history, and accounts of the author’s experiences. The resulting interpretations
recognize that food things are material markers of moments when a food’s habitual use is
interrupted by conflicting human-object engagements. Thus, food things are culturally significant
rather than literary props allowing food things to tell their own stories in the larger context of
history and culture
Physical Quantification of the Interactions Between Environment, Physiology, and Human Performance
No full textCharacterizing key physical interactions between the human body and an environmental
context has countless important applications in public health, preventative healthcare, city
planning, sports medicine, aviation, and more. However, the complexity of these multi-
faceted interactions makes physical first principles approaches challenging. This manuscript
presents a data-driven experimental paradigm that brings together holistic physical sensing
and a range of computational tools to generate empirical machine learning models that
quantify the interactions between environment, human physiology, and performance. The
two key products of this paradigm are, 1) high fidelity predictive models, and 2) objective
evaluation of predictor variable impacts on target variables. For example, in one case study,
particulate concentrations were accurately inferred from the biometric observations alone
using an empirical machine learning model. Next, evaluation model predictors revealed body
temperature as the most important predictor of particulate concentrations. This flexible
paradigm is used in multiple contexts to provide practical insights into the high-dimensional,
interconnected dynamics of environment, physiology and human performance
The Physical Characterization of Human Autonomic Responses and Health in a Variety of Environmental and Social Contexts
No full textThe human body responds to environmental stimuli in a variety of ways. Combining the
physical measurements autonomic responses such as eye movement, heart rate and sweat
response may provide a robust characterization of millisecond human interactions with the
surrounding environment. Furthermore, the environment directs health outcomes through
long-term exposures, which is explored in conjunction with hospitalization data. This thesis
also explores a method to detect blinks that would aid in quantifying concepts such as
cognitive load, and finally, a software suite for comprehensively analyzing brain, eye, and
audio data to dynamically explore the coupled nature of metrics and an application of these
techniques to a variety of everyday and specialized activities. Various machine learning
techniques are used to analyze this high-dimensional feature-rich data space and to automate
the extraction of interesting events
Precessional Effects on Gravitational Wave Data Analysis
No full textBlack holes (BHs) that closely orbit each other can form a binary black hole (BBH) system.
We can divide the lifetime of these BBH systems into three distinct phases: the adiabatic
inspiral, the merger and the ringdown. BBHs can emit gravitational waves (GW) during
every phase of their lifetimes. The spins of the individual BHs are expected to have non-zero
values and to be misaligned with the orbital angular momentum. This misalignment can
induce precession and nutation of the orbital angular momentum around the total angular
momentum. These phenomena modify the GW phase and amplitude. Efforts are underway
to quantify these effects via two spin parameters, χeff, χp, inside post-Newtonian (PN)
templates used in parameter-estimation methods. There are claims that precession has
been detected both statistically in the third observing run(O3) catalog, and in individual
systems like GW200129 but the consensus is not yet clear. We quantify precession and
nutation by introducing five new parameters. We believe these parameters may provide a
more complete characterization of the amplitude and frequency of precession and nutation as
binaries inspiral through the sensitivity band of GW detectors. We introduce the parameters
inside a PN template and study the modulation of the GWs. We then calculate the mismatch
between templates to determine the minimum signal-to-noise needed to identify precession
and in both the next LIGO collaboration runs as well as proposed future detectors.
Then we move on to the strong gravitational lensing of GWs which occurs when the GWs
from a compact binary system travel near a massive object. The lensed waveform is given
by the product of the lensing amplification factor F and the unlensed waveform. In the
geometrical-optics approximation, lensing produces at most two discrete images which can
be parameterized by two image parameters, the flux ratio I and time delay ∆td between
images. In the macrolensing regime for which ∆td is large compared to the time T they
spend within the sensitivity band of GW detectors, it is natural to parameterize lensing
searches in terms of these image parameters. The functional dependence of the lensed signal
on these image parameters is far simpler, facilitating data analysis for events with modest
signal-to-noise ratios, and constraints on I and ∆td can be found. We then propose that this
use of image parameters can be extended to the microlensing regime (∆td < T) in which the
two interfering images are observed as a single GW event. Finally, we use image parameters
to determine the detectability of gravitational lensing in GW the microlensing regime
La Genración “Yo No Me Dejo” Alternative Cuirness and Revolution in Puerto Rico
No full textIn 2019, the Puerto Rican LGBTQIA+ community engaged in peaceful direct actions such as
marches, strikes, and drag performance to protest the Puerto Rican administration. While many
subcultures participated in the movement that led to ex-governor Ricardo Roselló’s resignation,
the LGBTQIA+ community’s leadership and involvement were particularly influential. This
creative dissertation combines short fiction and traditional academic writing to demonstrate how
the Puerto Rican queer community used performative protest strategies to mobilize the masses
and dethrone a corrupt governor. By addressing the intersection of the Puerto Rican queer
community and political activism, my work demonstrates how this community is following in
the footsteps of revolutionary groups such as the Street Transvestite Action Revolutionaries by
weaponizing performance for the purpose of political upheaval. The academic chapter provides
the sociopolitical context for the creative chapters that follow delving into topics such as Puerto
Rico/U.S. relations, subcultural style, queer and performance theory, and creative criticism.
The creative portion of my dissertation engages fiction, in the style of Latin American
testimonio, to represent the LGBTQIA+ community of Puerto Rico who, because of a history of
marginalization, was in the perfect position to spearhead the revolutionary movement that led to
the governor’s resignation. The fictional narratives featured in my work are based on interviews
conducted with members of the Puerto Rican queer community. These narratives informatively
represent and comment on Puerto Rico’s real-life sociopolitical issues as well as the challenges
the LGBTQIA+ community faces which were exacerbated by Hurricane Maria and the exgovernor’s behavior
Strategic Management of Intellectual Property Rights and Technology Entrepreneurship
No full textIn the 1990s, investments in intangible capital began to outweigh tangible capital investments in
the United States. Firms have increasingly prioritized investment in research, development, and
commercialization of intangible assets over those of traditional or tangible assets. Creating and
capturing value from intellectual property (IP) have emerged as cornerstones of successful
innovation and entrepreneurship. According to the United States Patent and Trademark Office,
there were 127 IP-intensive industries in 2019, and these industries accounted for 41% of U.S.
GDP (approximately 7.8 trillion USD) and 44% of U.S. employment (approximately 62.9
million jobs). As President Abraham Lincoln (1860) once remarked, the patent system added the
fuel of interest to the fire of genius.
Value creation and appropriation through intellectual property are among the most vital
determinants of firm performance and growth potential. Both entrepreneurial and established
firms strive to coordinate their inventive activities, not only to create but also to appropriate
value from their inventions. Value appropriation generally involves many intermediate steps over
the long term before transforming a firm’s creation into an end product. A firm strategically
patents inventions to protect certain of its IP rights. A patented invention is a nonobvious, novel,
and practical solution to a given technological problem. In return for publicly disclosing
information about the invention, thus advancing our current understanding of the technical
problem and promoting knowledge creation, an innovator receives a patent’s exclusive legal
rights, requiring others to obtain permission for the use of this invention for a limited period of
time. Although varying widely across industries and countries, this monopolistic right can confer
a competitive advantage on an entrepreneur as well as a firm. As such, particularly in
technology-intensive sectors, firms strategically patent and manage their IP rights as a
mechanism for value creation and capture. The nature of IP and the way that it is generated can
shape the choice of IP protection by influencing the firms’ current rights and expectations.
However, going beyond the extensive prior studies on technology and innovation management,
relatively limited research has explored firms’ strategic management of IP rights and technology
entrepreneurship. In my dissertation, I examine firms’ ex post IP management strategy and
technology-based entrepreneurship to delve into how entrepreneurial firms strategically create
and capture economic value from innovation investments.
In Chapter 1, I explore the role of IP rights in organizational decision-making by examining
patent renewal management. Given that the potential value appropriation of technological
inventions is highly uncertain, firms may regard filing a patent as if they were purchasing a real
option. After the grant date, firms holding patents must periodically decide whether to extend
their options (by paying renewal fees) or to abandon these options. Extending such real options
preserves their rights to exclude others from using the inventions. Examining the renewal
decisions for the population of over 2 million U.S. patents granted between 1990 and 2018, I find
that firms are more likely to extend options by renewing those patents that present (1) greater
breadth in terms of technological opportunities, (2) those situated in fragmented technology
markets, and (3) in areas with a fast technology cycle time. In contrast, firms are more likely to
abandon options by letting expire those patents with a high level of technological novelty. The
findings provide new insights on how key technological attributes could affect organizational
decisions differently at the time of exercising options rather than at the time of obtaining options.
In Chapter 2, I provide a framework for understanding firms’ decisions to transfer patent
ownership to another firm in the markets for innovation. I predict that the closer proximity of a
patent’s technology structure to that of a firm’s patent portfolio generally results in greater
marginal productivity from that patent, leading to future economic return for the firm. By
employing a dyadic-level analysis of transactional decisions on 40,110 patents assigned to 57
leading biopharmaceutical firms between 1987 and 2016, I find that firms are more likely to
trade patents when the technology structure of a patent is closer to the technology stock of a
potential buyer relative to that of the original assignee. The framework also considers a set of
boundary conditions in which interfirm IP transactions take place. I find that a relationship
between relative technological distance and each buyer-assignee dyad is likely to be weaker
when a potential buyer and the assignee are in the same industry or when the assignee has high
technological capability. I discuss how these findings could stimulate patent trade for both
entrepreneurial and established firms in the markets for innovation.
In Chapter 3, I examine how digitization of inventive records reshapes entrepreneurial
innovation and innovation diffusion. Although inventive activities rely on recombining prior art,
accessibility and identification of relevant prior art incur considerable search costs. I therefore
exploit a natural experiment to delve into how a sudden reduction in search costs—in this case,
the 2006 launch of Google Patents digitizing inventive records—affected the productivity,
nature, and diffusion of entrepreneurial innovation. Using a difference-in-differences approach, I
examine the inventions of 19,190 U.S.-based startups in the life sciences industry. I find that
digitizing records of inventions increase the startups’ invention productivity, without
compromising invention quality, as the geographic distance from a United States Patent and
Trademark Office archive grows. Moreover, digitization not only stimulates invention crossfertilization as innovation input but also expands invention breadth as innovation output for
startups located at a distance from the archives. Furthermore, the pace and scope of innovation
diffusion increase when inventions receive early attention within the life sciences community.
This study sheds new light on how digitization reshapes entrepreneurial innovation