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Essays on Corporate Bankruptcy and Debtor-in-possession Financing
No full textThis dissertation consists of two essays in financial economics. The first essay, included in
Chapter 2, concerns the effect of debtor-in-possession (DIP) financing and DIP financing
lenders on the outcome of Chapter 11 bankruptcy. When firms file for protection under
Chapter 11 bankruptcy, their access to outside financing will be limited. The Bankruptcy
Reform Act of 1978 has resolved this issue under section 364 of the US Bankruptcy Code by
defining laws for the DIP financing, which is the unique type of financing available to firms
filing for Chapter 11 bankruptcy. DIP financing is usually senior to all other securities issued
by a firm and violates the absolute priority rule by standing ahead of a company’s existing
debts for payment. Among the characteristics of DIP financing, limited attention has been
given to the type of lender of the DIP financing. There is not much empirical evidence on
whether financing a DIP loan from different types of lenders can lead to different bankruptcy
outcomes. In this essay, I investigate the role of DIP financing, especially the DIP lender in
the bankruptcy process. I provide evidence for the role of DIP lender, bank versus non-bank,
in bankruptcy outcome, while controlling for potential endogeneity of the lender’s type. In
order to control for the endogeneity of the DIP lender type, I use an instrumental variable
(IV) approach. My results show that even after controlling for the endogeneity of the lender
type, the source of the DIP loan still matters for the outcome of the bankruptcy process.
More specifically, receiving the DIP loan from banks increases the likelihood of emerging
from bankruptcy as a going concern for the bankrupt firm.
The second essay, included in Chapter 2, concerns predicting bankruptcy outcome using a
machine learning approach and using the bankruptcy outcome predictions to predict firms’
CDS spreads. First, I develop a machine learning model using Extreme Gradient Boosting
to predict the outcome of the bankruptcy. I compare the performance of this model with
that of a traditional logistics regression model and show that, while both perform well, the
machine learning model outperforms the traditional model, mainly because it is able to
identify non-linear patterns in the data. I, then, use the predicted probabilities of emerging
from bankruptcy, combined with the predicted probabilities of bankruptcy, produced by a
second machine learning model, to predict CDS spreads. I show that the predicted probability
of bankruptcy and probability of emerging from bankruptcy can be used to predict firms’ CDS
spreads and can improve the prediction power of benchmark models. This study contributes
to the bankruptcy and bankruptcy outcome prediction literature by providing empirical
evidence of the association between a firm’s characteristics and its bankruptcy outcome. I
also show that using machine learning techniques to predict the bankruptcy outcome can
help predict CDS spreads more accurately
Atomic-scale Characterization of Surface and Interface Dynamics in Novel Materials: Cr2Ge2Te6, NbSe2, and Strontium Barium Niobate
No full textTransition metal dichalcogenides (TMDs) and transition metal trichalcogenides (TMT) are
promising layered materials for novel electronic and optoelectronic device applications due to their
fascinating electronic, optical, magnetic, and chemical properties with two dimensional (2D)
atomic limits. However, their thermal stability and thermally induced defects, which are crucial
for reliable operation of the devices, remain an area for further investigations.
The electro-optic (EO) materials with high Pockels coefficient are also an intriguing research field
for fast, small, and low power consumption electro-optical devices. Integrating the EO materials
on the current silicon technologies is challenging due to demands for high crystal quality and
sensitivity to orientation but highly desirable to expand their application field with compact design
and low power consumption.
This dissertation focuses on the thermal stability and thermal evolution studies of 2(TMD)
and 226 (TMT) at the surface and material interface by employing in-situ scanning
transmission electron microscopy (STEM) to probe the dynamics of thermal evolution and defects.
The interface and surface of molecular beam epitaxial (MBE) grown strontium barium niobate on
silicon with strontium titanate buffer layer is also investigated using STEM to understand the
nature and growth mechanism
Why Do Firms Hide Customer Identities? An Accounting Manipulation Explanation
No full textPrior studies document that firms withhold about 40% of customer identities and attribute this
practice to proprietary cost concerns. In this study, I propose a new economic reason for firms’
concealment of customer identities. I argue that when firms manipulate accounts related to
customers, namely revenues and accounts receivable, they have incentives to conceal customer
identities to reduce the likelihood of detection. Consistent with this argument, I find in a differencein-differences analysis that firms engaging in fraud related to revenues and accounts receivable
reduce the disclosure of customer identities by 26% during the fraudulent years, relative to firms
engaging in other types of fraud. The effect is more pronounced when managers have personal
gains from the fraud, when firms have stronger relationships with their customers, and when firms
face greater external monitoring from analysts and institutional investors. I also find that fraud
detection risk is lower for firms that conceal customer identities than for firms that do not,
consistent with the benefit of hiding customer identities
Informing Surgical Interventions via Biomechanical Engineering Techniques for Individuals With Lower-limb Loss and Pathology
No full textAmputations (i.e., limb loss) and osteoarthritis are two of the leading causes of long-term
disability. Persons within these associated populations suffer from gait abnormalities and pain,
which lead to a lower quality of life. Individuals with transfemoral amputation who are ambulatory
don prosthetic sockets that often need frequent clinical refitting/reconfiguration and have few
realistic alternatives, especially in individuals with obesity and/or vascular disease. To overcome
these issues, osseointegration, or direct skeletal attachment of a prosthesis to a limb, has been
proposed and shown to greatly improve functional mechanics of the lower-limb. But
osseointegration surgery has only be used on patients with traumatic limb loss (representing the
minority of the population) and can lead to infection of limb soft tissue and bone that requires
additional amputation surgery and loss of limb length. Medial thighplasty, or excision and
liposuction of adipose tissue in the residual limb, is a more conservative surgical alternative with
higher eligibility than osseointegration and that may also improve prosthetic function. However,
this limb “recontouring” procedure is often viewed as a surgery that improves limb cosmesis (i.e.,
its appearance), as opposed to its function. In fact, most medial thighplasty candidates are non
amputees who are obese. This dissertation evaluates the influence of medial thighplasty surgery in
the context of transfemoral limb loss and quantifies improvements in lower-limb and center-ofmass kinematics and kinetics during straight-line walking as well as during transient changes of
direction. This surgical technique—modifying only the limb adipose tissue—improved
biomechanical function and maneuverability characterized by greater path efficiency, faster
movement completion times, smoother turning curvatures, tighter coupling between movement
velocity and curvature, and increased shear ground reaction forces. This work suggests that
confidence and fluidity of movement can be improved if medial thighplasty is applied in
individuals with transfemoral limb loss and provides a missing link between the underlying
structure of the residual limb and the function of lower-limb prostheses. Osteoarthritis has been
shown to be secondary to developmental joint abnormalities, which are often expected to lead to
higher contact stress of the articulating joint surfaces. Dysplasia and femoroacetabular
impingement are two common hip deformities that lead to premature joint degradation. Yet,
diagnosis is complex, and the course of treatment is different depending on the pathology. A robust
treatment plan for therapy or surgery is vital to preserving the hip joint before the onset of
osteoarthritis. This dissertation evaluated patients with diagnosed dysplasia or impingement prior
to hip preservation surgery and uncovered significant differences in their gait biomechanics. The
dysplasia cohort exhibited widespread gait deviations throughout the stride, while impingement
group showed localized differences in mechanics that primarily occurred during peak hip
extension (i.e., last stance phase of the stride). Furthermore, this dissertation investigated the use
of dynamic simulation of static medical imaging from these patients. We argue, as an alternative
to dynamic imaging modalities, that imposing normative motion of these static joint images in a
simulation framework can lead to further insight about the underlying root causes of each
deformity and calculate geometric properties of the hip center-of-rotation, as well as inadmissible
variations of the relative motion between femur and acetabulum during normative level and sloped
walking. Finally, continuous classification schemes were evaluated (linear and nonlinear
discriminant analyses) to probe the separation between time-varying features of these multiple
pathologies that occur throughout the stride. These final studies pertaining to hip preservation also
deepen our understanding of the functional link between lower-limb structure and its function
during widely varying ambulation scenarios and provide a potentially powerful tool to improve
the diagnosis and treatment of a given patient
Dentification of Novel Regulators of Nitrate Respiration in Paracoccus Denitrificans: Roles of DksA, (p)ppGpp, and RegAB
No full textParacoccus denitrificans is a metabolically versatile Gram-negative alpha-proteobacterium that is
used as a model organism for studying respiratory metabolism. One of the most notable features
of P. denitrificans is its capacity to use nitrate or nitrogen oxides as terminal electron acceptors in
the process of denitrification, which is the sequential conversion of nitrate (NO3-) to gaseous
dinitrogen (N2). The P. denitrificans genome encodes three members of the DksA/TraR family of
transcription factors, two of which appear to be bona fide DksA proteins (hence designated
DksA1Pd and DksA2Pd). There is a single relA/spoT gene in the genome encoding a predicted
bifunctional (p)ppGpp synthetase and hydrolase (designated RSH, for RelA/SpoT Homolog). Both
DksA1Pd and DksA2Pd can rescue the amino acid auxotrophy of an Escherichia coli dksA mutant.
Deletion of either dksA1 or relA/spoT eliminates the upregulation of expression of the periplasmic
nitrate reductase (NAP) that is seen when cultures are grown on a reduced substrate such as
butyrate. Thus, we conclude that DksA1Pd and (p)ppGpp activate nap transcription in response to
growth on a reduced substrate and that these proteins therefore help to maintain redox homeostasis
by activating a mechanism for the disposal of excess reductant. Moreover, we show that the redox-
sensing RegAB two-component pair acts as a negative regulator of nap expression under anaerobic
growth conditions. Under the same conditions, RegAB acts as a positive regulator of the
expression of the membrane-associated nitrate reductase Nar, mediating reciprocal regulation of
the two nitrate reductases that have distinct physiological roles.
The dksA1 and relA/spoT genes are conditionally synthetically lethal; the double mutant has a null
phenotype for growth on butyrate and other reduced substrates while growing normally on
succinate and citrate. The flavohemoglobin gene hmp is modestly upregulated in dksA2 and
relA/spoT mutants, which are also defective for biofilm formation (possibly because of enhanced
scavenging of nitric oxide). In conclusion, we have successfully identified two functional DksA
homologs in P. denitrificans - DksA1Pd and DksA2Pd, along with a (p)ppGpp synthetase homolog
(RSH) and a two-component RegAB system. These regulators were previously unknown and
found to be responsible for regulating the expression of enzymes involved in nitrate reduction and
nitric oxide metabolism
Essays on Digital Entrepreneurs’ Strategic Categorization Strategies
No full textRandy Lau, a passionate filmmaker and storyteller from California, finally started his own
YouTube channel, "Made with Lau," aiming to share his dad’s Chinese recipes and family
stories in September 2020. Randy lost his job during the COVID-19 pandemic, and his family
was expecting a new baby then. The financial pressure and free time during the quarantine
inspired Randy to share recipes of his dad, who has over 50 years of experience cooking in
Chinese restaurants, on YouTube to make earnings. After navigating the initial uncertainties and
fluctuations, Randy’s channel skyrocketed to amass 400,000 subscribers and generated an
average monthly revenue of $50,000 within a year. Randy now has become a full-time YouTuber
and works with a small team in creating and editing videos. The entrepreneurial success of
Randy on the YouTube platform is not unparalleled. The rise and popularity of digital platforms
such as YouTube and Twitch have provided great opportunities for entrepreneurs to explore their
talents and share quality content while earning a living.
The anecdotal success of “Made with Lau” motivates one exciting research question in the field
of digital entrepreneurship: How do digital entrepreneurs like Randy establish and sustain their
businesses in such a competitive and dynamic environment? Specifically, what types of content
strategies do they apply, and how do they pivot strategies based on market trends and audience
feedback? Motivated by these questions that new digital entrepreneurs face, this dissertation
explores how entrepreneurs apply and pivot their content strategies on digital platforms and its
performance implications. This dissertation encompasses three chapters to examine this broad
question, followed by a conclusion section.
Chapter 1 is an introductory chapter where I review prior literature on digital entrepreneurship
through the lens of organization theory such as optimal distinctiveness(OD)and cultural
entrepreneurship. I also identify the gap in the literature to motivate the remainder of the
dissertation.
Chapter 2 examines how YouTubers can incorporate their personal identity, their persona, into
the digital content and enhance the effectiveness of category spanning strategies. Whereas
category-spanning has been regarded as legitimacy-deducting and would harm producers’
performance, I found that if digital entrepreneurs can anchor their persona identity into content
and establish para-social relationships with their audience, the category-spanning strategies may
enhance their performance.
Chapter 3 investigates the categorization strategies of nascent entrepreneurs (YouTubers) after
they enter the market. Specifically, I examine the effectiveness of conforming to two types of
reference points: category exemplars and past self. Whereas both strategies can enhance the
performance of entrepreneurs, simultaneously pursuit of both could jeopardize it. In addition, the
effectiveness of upholding a consistent identity would decay with the age of the channel. This
study provides insights to cultural entrepreneurship and categorization literature.
In conclusion, I summarize the key insights generated from the dissertation, its contribution,
limitations, and directions for future research
Seismic Rock Physics Analysis of Organic-rich Shales Using Statistical and Machine Learning Methods
No full textShale is the most common sedimentary rock, which accounts for approximately 70 percent
of the rocks in the crust of the Earth. In a conventional petroleum system, organic-rich
shales have been regarded as source rocks generating hydrocarbon resources. Over the past
decade, these shale rocks have become both the source rocks and unconventional reservoirs
because of the combination of horizontal drilling and hydraulic fracturing. Although drilling
and development technologies have been advancing rapidly, there is a lack of exploration
involved with many shale resource operations. The current ’drilling on a grid’ strategy causes
inefficient hydrocarbon production and unnecessary expense because many shale reservoirs
are more heterogeneous and complex than conventional sandstone reservoirs. To identify
shale reservoir production ’sweet spots’ from seismic data to help optimize recovery, we need
to develop more e↵ective seismic reservoir characterization methods. Also, we have to reduce
the impact of greenhouse gas emissions and associated climate change while developing
unconventional oil and gas. For this reason, we need a better rock physics model (RPM)
to describe shale reservoirs and understand their heterogeneity or anisotropy. However, in
contrast to conventional sandstone reservoirs, many important shale reservoir rock physics
properties are not well understood. Moreover, the connections between seismic, elastic, and
shale rock properties are complex and need more research to improve quantitative inversion and interpretation of seismic data. There are two main geophysical problems for better
shale characterization: (1) building a proper seismic RPM of organic-rich shales, and (2)
estimating accurate shale-specific reservoir properties from seismic data. To help integrate
these multi-disciplinary concepts, this dissertation proposes three topics as part of my PhD
research: (1) Improved shale RPM methods to estimate the total organic carbon (TOC) and
mineralogical brittleness index (MBI) using statistical and machine learning methods, (2)
Seismic amplitude variation with o↵set (AVO) forward modeling and AVO attribute analysis
to model an accurate synthetic seismic data and predict important shale properties such
as TOC and clay volume, and (3) Enhanced seismic anisotropy characterization methods
to estimate shale reservoir properties from anisotropic seismic data. Therefore, successful
estimation of shale rock properties from seismic properties may allow us to better characterize
the organic-rich shale rocks. Also, these approaches can interpret the e↵ect of variations in
porosity, mineralogy, and organic carbon concentration on seismic property changes. In
conclusion, these methods potentially improve the shale reservoir characterization and time-
lapse monitoring for shale hydrocarbon production. They can also help to provide seismic
rock physics frameworks for accurate interpretation and monitoring of the physical property
changes, for example, during CO 2 enhanced oil recovery (EOR), carbon capture and storage
(CCS), and geothermal energy production
Diamonds in the Rough: an Outcomes Evaluation of a Juvenile Sexual Exploitation Court
No full textCommercial sexual exploitation (CSE) affects many people across the globe. Of utmost concern
is that many children become victims, or are at risk of becoming victims, of sexual exploitation
and are often only identified upon contact with the juvenile justice system. While these youth
were historically processed through the traditional juvenile justice system, diversionary courts
addressing CSE have been developed as a less punitive response to this unique population.
diversionary courts provide a more treatment-oriented response, though it remains unclear
whether these courts are effective for sexually exploited youth. This dissertation utilizes data
from a large urban Texas county to conduct an outcomes evaluation on the E.S.T.E.E.M.
(Experiencing Success Through Empowerment, Encouragement, and Mentoring) court program.
This program contains four phases that last approximately 30 days each, for a total of about 180
days. These four phases in ascending order are Sapphire, Emerald, Ruby, and Diamond. The title
of this dissertation is a reflection of these various phases that female youth promote through.
This play on words, “Diamonds in the Rough,” typically represents an individual that has
immense potential that has not been developed enough. It is through the E.S.T.E.E.M. court that
youth are given the tools to be deterred from delinquency and future CSE victimization. In this
dissertation, recidivism is operationalized as local outcomes subsequent referrals, subsequent
detentions, and subsequent supervisions) and re-arrests. The analysis aims to determine whether
youths who participate in the E.S.T.E.E.M. court program are less likely to recidivate than youth
who do not participate. A survival analysis is also conducted to determine the celerity of re-arrest
for program participants versus non-participants. Factors associated with post-program re-arrest
are examined at 12 and 24-month follow up periods. Post-hoc analyses explore descriptive
longitudinal statistics related to re-arrests for program participants, reasons for non-participation,
and reasons for unsuccessful program discharge. This dissertation adds to the literature by
determining whether the analyzed population of youth is best served by specialty court
programming and by identifying significant predictors of re-arrest for court participants.
Recommendations for E.S.T.E.E.M. court include integrating trauma-informed approaches to
care, allowing youth’s voice to play a role in identifying individual goals, services, and resources
that are most efficacious, and ensuring that the risk-needs-responsivity (RNR) framework is
utilized when considering types and frequencies of expectations/services provided
Structural Heterogeneity in Neuronal Aging: Insights From Micro and Macro Structural Neuroimaging
No full textNeuroimaging research is making unprecedented gains towards a better understanding of what
constitutes healthy brain structure and function in aging. Decades, if not centuries, of ex vivo
histological work have demonstrated the complexity of cytoarchitectural and myeloarchitectural
underpinnings of neuronal organization that we are only beginning to investigate in the living
brain. With advancing techniques, we can now investigate in vivo estimates quantifying
biological proxies of structural brain health. The current studies aimed to capitalize on both our
histological understanding of the architectural features defining brain structure, and modern
neuroimaging estimates of structural health, to expand upon our understanding of the processes
involved in nominal brain aging. In a healthy lifespan sample of adults, we acquired multiple
neuroimaging sequences designed to characterize the health of gray and white matter tissue
compartments. By mapping these estimates to a cytoarchitecturally defined brain atlas we were
able to 1) examine the regional differentiation of the coupling of gray matter morphometry and
health proxies from the neighboring white matter most likely to innervate these regions and 2)
investigate the age-related associations between estimates of neurite health and organization
within the gray matter of specific cortical types. We found that there were regionally distinct
patterns of association that generally pointed to an age-related vulnerability of structure in
higher-order cognitive centers. These regions demonstrated greater coupling in morphometry
with neighboring white matter health proxies, as well as elevated organizational heterogeneity
within these cortical types. Our results demonstrate that aging trajectories in brain structure
follow specific patterns that map on to several key theories posited in prior research such as
retrogenesis, phylogenetic, or ontogenetic precedence. However, these findings provide novel
evidence emphasizing the importance of myelin content and plasticity as well as the role of glia,
specifically oligodendrocyte function, and the high cost of brain maintenance, prompting further
investigation of additional conceptualizations of structural brain aging
Semantic interference and facilitation: the role of feature cues and category in naming
No full textSemantic interference effects have been observed in a variety of naming paradigms where
categorically related items, (i.e., cow, horse, sheep), elicit longer naming latencies than
categorically unrelated items (i.e., book, knife, mirror). However, under certain conditions,
semantic facilitation effects (i.e., shorter naming latencies) may be observed from categorically
related items depending on the context and order of presentation within a paradigm. Semantic
interference and facilitation effects observed in naming are also proposed to be differentially
influenced by the correlational nature of the features that comprise these concepts.
Using a lexically cued naming paradigm with word pairs designated as either “distinctive” or
“shared” features to elicit a target concept which was either related to other concepts within a
category or not, evidence for semantic facilitation effects were found for concepts from
categorically related items (e.g., farm animals, zoo animals, pets, etc.) when cued by distinctive
features. Interestingly, semantic interference effects were not observed in a lexically cued
naming paradigm. Likewise, event-related potentials (ERPs) were evaluated, and a significant
effect of category (related vs unrelated) was found in the left frontotemporal and right
centroparietal regions between 600-1100ms. These ERPs are proposed to represent in the
initiation of feature integration beginning approximately 600ms following stimulus presentation
and approximately 1200ms prior to naming, indicating an amplitude divergence between
categorically related and unrelated concepts. Given the behavioral and EEG data, the following
account of semantic and lexical processing is proposed: Categorically related concepts facilitate
semantic processing at the superordinate level (i.e., categorical or domain) and features of
concepts less likely to co-occur with other concepts (i.e., “distinctive” features) facilitate
activation of concepts at the basic level (i.e., specific concept) as measured by naming. Frequent
activation of features common among related concepts facilitate subsequent activation of related
concepts which facilitates superordinate level semantic processing and distinctive feature cues
facilitate access to the basic-level identification required for naming. Categorical level effects are
shown to influence naming and neural correlates and when related concepts (or concepts with
increased activation of features) are cued by distinctive feature cues, naming latencies and errors
are decreased compared to other conditions. Our results suggest when facilitation occurs at both
superordinate and basic levels of conceptual processing, naming performance improves