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Lyapunov-Based Nonlinear Control Strategies for Manipulation of Particles and Biomolecules Using Optical Tweezers
No full textTweezers-based nanorobots, optical tweezers in particular, are renowned for their exceptional
precision, and among their biomedical applications are cellular manipulation, unzipping
DNAs, and elongating polypeptide chains. This thesis introduces a series of Lyapunov-based
feedback control frameworks that address both stability and controlled instability for biological
manipulation, applied within the context of optical tweezers. At the core of this work are
novel controllers that stabilize or destabilize specific molecular configurations, enabling fine
manipulation of particles like polystyrene beads and tethered polymers under focused laser
beams.
Chapter 1 covers the foundational principles and surveys existing literature on the modeling
and control of optical tweezers, emphasizing gaps in the stability and instability control
of molecular systems. Chapter 2 presents a robust Control Lyapunov Function (CLF)
approach, designed to stabilize spherical particles under optical trapping. By formulating a
smooth, norm-bounded feedback controller, we achieve lateral stabilization despite external
disturbances, using a real-time, static nonlinear programming (NLP) solution. Simulations
verify the effectiveness of this CLF framework, even with significant initial displacements
from the laser focus and under thermal forces modeled as a white Gaussian noise.
Chapter 3 addresses controlled instability through a Control Chetaev Function (CCF)
framework, specifically targeting protein unfolding applications. Linearization with respect
to the control input facilitates the application of destabilizing universal controls for affine-
in-control system dynamics. The resulting CCF-based norm-bounded feedback controller
induces system instability by laterally extending the trapped DNA handle, thereby increasing
the molecular extension and providing insights into protein denaturation and unfolding
pathways. This controller is robust to stochastic thermal forces and optimized for real-time
computational efficiency.
These Lyapunov and Chetaev-based control designs collectively expand the capabilities of
optical tweezers, advancing single-molecule manipulation under both stable and unstable
conditions. These findings advance precision nanomanipulation, opening new avenues for
exploring the molecular mechanics of protein unfolding and DNA elasticity
Heaven Imagined in Literature: Dante’s Paradiso Reimagined in the Works of C.S. Lewis and Olaf Stapledon
No full textThis dissertation will examine the reception and transformation of Dante’s Paradiso, meaning,
the reception of the medieval imaginative vision of the Heavens by two modern artists, C.S.
Lewis and Olaf Stapledon. In The Discarded Image, C.S. Lewis presents the medieval
cosmological model to a modern audience as the “supreme medieval work of art,” the artistic
backdrop and assumed context of Dante’s Comedy, particularly the Paradiso. In the Paradiso,
Dante creatively reinterpreted both classical and medieval texts. Likewise, both Lewis and
Stapledon were twentieth-century British artists and academics who reinterpreted Dante’s
Paradiso within their own contemporary cosmic fictions. Both Lewis and Stapledon recaptured
the medieval poetics of the cosmic narrative of the Heavens, the medieval mystic quest, and the
theme of transfiguration in Dante’s Paradiso. However, morally and philosophically, Lewis’ and
Stapledon’s literary transformations produced two very different outcomes. Lewis, attempted to
recapture the emotional effect or the comedy of the medieval Heavens, and therefore challenged
the reader’s expectations of the medieval Heavens and proposed by his experiment to try and
recapture as much of the medieval imagination as possible. On the other hand, Stapledon
completely transformed his reading of Dante, just as Dante transformed the classical works
before him, and thereby produced a tragic reception of Dante’s Paradiso. And yet, although
Stapledon does preserve Dante’s image of a direct encounter with the Divine, he instead presents
an apathetic Creator, the complete reversal of Dante’s and Lewis’ depiction of the Divine as
Love. Still, both Lewis and Stapledon wrote modern myths which aimed to recapture the
medieval interior quest or the soul’s journey towards the Divine
Noise: Waves on the Edge
No full textNoise is a multipart multimedia experience utilizing live ambisonics, projection, lighting, and
sculpture to disrupt the institution of traditional art and live production. This work will ask
participants to interact with five sound sculptures that will evolve over the exhibition to
showcase the participants and what they provide to the work. By taking simple sound principles
and incorporating them into sculpture, it allows the audience to relate and interact with the
everyday sound around them. During the exhibition, I will further the idea of everyday Noise by
utilizing field recordings and electronics to create a live ambisonic performance around the
audience
Advanced Bearing Condition Monitoring for Electrical Machines
No full textEffective condition monitoring of bearing faults in electrical machines is vital for ensuring
industrial reliability and optimal performance. Bearings, as crucial components, facilitate
the smooth operation of rotating machinery, such as motors, by supporting the rotor and
maintaining a consistent air gap. Bearing faults, particularly distributed faults, are a major
contributor to machinery failures. Timely detection and diagnosis of these faults are essential,
as undetected issues can result in unplanned downtime, significant repair expenses, and, in
severe cases, catastrophic equipment failure.
Bearing faults generally emerge due to gradual wear and tear, with distributed faults
triggered by factors such as insufficient lubrication, contamination, or electrical erosion.
Unlike localized faults, which are confined to a specific area of the bearing and are more
easily identified through conventional methods, distributed faults pose a greater challenge
for detection. These faults affect multiple areas of the bearing simultaneously, creating
complex and unpredictable patterns that complicate the diagnostic process. In industrial
environments, where bearings are subjected to varying loads and speeds, the challenges
of detecting distributed faults become even more pronounced. While traditional condition
monitoring methods are effective for localized fault detection, they are less reliable for
identifying distributed faults, particularly under variable operating conditions. These methods
may fail to capture the subtle, widespread nature of distributed faults, making it difficult
to ensure the longevity and reliability of electrical machines. Hence, there is an increasing
demand for advanced condition monitoring techniques capable of more accurately detecting
and diagnosing distributed bearing faults, thereby ensuring the performance and extending
the operational lifespan of industrial machinery.
This dissertation focuses on detecting and classifying common distributed bearing faults in
industrial settings, specifically in low- and high-power motors, through the analysis of both
electrical and mechanical signals. The research begins with an in-depth study of vibration
signals under both healthy and faulty conditions, encompassing localized and distributed
bearing faults. These distributed fault patterns were systematically generated in a controlled
laboratory environment, allowing for a thorough analysis of vibration spectra. Particular
attention is given to the characteristics of distributed faults, which result from random defects
spread across the bearing surfaces. Additionally, specific formulae are introduced to detect
vibration signal signatures associated with these faults.
Deep learning architectures are subsequently proposed to detect and classify distributed
bearing faults. This is achieved through fusion analysis, utilizing vibration signals, stray mag-
netic flux signals, and motor current signals. For low-power motors, a real-time, low-resource
algorithm designed for microcontrollers is developed using motor current data to identify
the most prevalent bearing faults. The study examines distributed bearing faults caused
by lubrication and contamination across seven low-power motors, tested under no-load and
fan-load conditions at ten different speeds, with controlled bearing aging. Key time-domain
features, such as Root Mean Square (RMS), peak values, and crest factors of motor current,
are analyzed to develop the proposed algorithm. The algorithm is thoroughly evaluated
in various experimental scenarios using the TI F280049 microcontroller and compared to
a baseline machine learning model. It demonstrated significant efficiency, requiring five
times fewer instruction cycles and half the memory resources compared to the standard
machine learning model. Furthermore, an enhanced deep learning-based model is proposed
for estimating the remaining useful life (RUL) of bearings in low-power electrical machines
using motor current signal analysis. This model achieved a remarkable accuracy of 95%,
underscoring its effectiveness in predicting bearing lifespan
Antiblackness in Egyptian Cinema and Arab Premodern Textual Heritage
No full textThis dissertation explores the similarities between racial notions of Black people in premodern
Arabic texts and in Egyptian cinema. For example, premodern texts described Black people as
uncivilized, primitive, less human, and less intelligent, among other negative attitudes. Both
early and modern Egyptian films have notable parallels with these premodern racial views,
representing Black characters as second-class citizens, troublemakers, criminals, subordinate,
unintelligent, and hypersexual. I examine portrayals in eight Egyptian films released from 1938
through 2012 and analyze how antiblackness has continued to appear on screen due to the legacy
of slavery in the Arab world, racial ideologies in the region, sociopolitical challenges in Egypt,
and a lack of deconstruction of these racial stereotypes at the academic level
Synthesis and Bioactivity Evaluation of KDM4 Inhibitors in Prostate Cancer Cells
No full textThe need for alternative therapeutic targets has grown due to the stagnating progress of treatment
for metastatic prostate cancer with activity independent of the androgen receptor. Inhibition of
histone lysine demethylases belonging to the KDM4 subfamily are of significant interest due to
their aberrant expression and role in castration-resistant prostate cancer. This dissertation presents
the design, synthesis, and biochemical evaluation for a library of 8-hydroxyquinoline-based
derivatives of B3, a KDM4 inhibitor that has previously demonstrated therapeutic potential.
Motivated by the search for improved efficacy for KDM4 inhibition in prostate cancer, the first
investigation highlights the structure-activity relationship discovered from modifying the
phenylpropyl moiety of B3. Screening a comprehensive list of different chemical groups revealed
several with improved inhibitor activity and stability. Continuing our search for improved efficacy,
the second investigation explored augmentation of the benzamide moiety of B3 that led to the
identification of a new lead inhibitor using 4-(3-methoxypropyl)morpholine. This modification to
B3 led to the desired cytotoxicity to tumor viability during in vitro MTT assays and in vivo murine
studies
Causarum Cognitio: the Architecture, Collections, and Social Agency of Three American Athenaea: Redwood, Boston, and Caltech
No full textIs the athenaeum an adaptable concept in the twenty-first century university environment? What
evidence exists to conclude that it contributes to a discursive community? This dissertation
explores the legacy of the concept of the athenaeum in America and examines the organically
formed social circles who share an interest in continuing discourse, often within multiple
disciplines, and who contribute to their communities by modeling habits and behaviors reflecting
their desire for improvement of themselves and their communities.
From before and since our nation’s founding, the societies of the American Athenaeum have
served as community-organized intellectual and artistic hubs, providing access to information,
pursuing thought-provoking discourse, and applying their aggregate knowledge resources as
agency for social change while presenting the most inspirational architecture, lectures, artistic
performances, and collections to their communities.
I focus on the eighteenth century Redwood Library and Athenaeum of Newport, Rhode Island,
the nineteenth century Boston Athenaeum, and the twentieth century Caltech Athenaeum. The
newest of these, Caltech Athenaeum, has been in service over one hundred years, and the oldest,
the Redwood Library and Athenaeum, has been in service to its community continuously over
300 years
Risk-based Motion Planning and Control for Robotic Systems
No full textA robot autonomy stack usually consists of several modules that enable it to perceive the
environment and decide how to interact with it to achieve a desired task. At the heart of
this stack are the motion planning and control modules. The motion planning module is
generally responsible for decision making and generating a plan for the robot to follow, such
as determining how an autonomous car should drive around pedestrians and other vehicles.
The control module computes a finer sequence of control actions that can be issued to the
actuators to operate the robot.
One issue that plagues robot motion planning and control is the effect of uncertainty, of which
there are different types, on the system. This includes unknown and unmodeled disturbances
that affect the system such as noise, aerodynamics, or simplified dynamics models. However,
addressing these uncertainties is non-trivial and often requires a trade-off between accounting
for the uncertainty accurately and the tractability of solving the problems.
This dissertation develops risk-based solutions for a few robot motion planning and control
problems. The contributions of the dissertation are categorized into four main types.
The first part addresses control design with complex spatio-temporal requirements under uncertainty. An optimization-based control algorithm is designed to guarantee the completion
of the requirements when the robot dynamics are affected by process noise.
The second part addresses sampling-based motion planning under uncertainty. RRT*, a
famous motion planning algorithm in robotics, is considered and risk-aware variants of it are
developed to account for process and measurement noise affecting the robotic system.
The third part addresses a limitation of learning-based planning approaches with an application to multi-agent motion planning. A reinforcement learning (RL) framework is considered
for learning policies then an optimization-based module, called a safety filter, is proposed to
enforce collision avoidance as hard constraints, which learning algorithms cannot do. The
safety filter is designed to handle process, state, and measurement noise.
Finally, the fourth part addresses data-driven planning in dynamic and uncertain environments. This assumes that the robot has access to some future predictions of the obstacles in
the environment, such as where they may be in the next few seconds. A safety filter is then
developed using these sample predictions to plan a safe trajectory for the robot.
In several sections, uncertainties whose distribution is unknown, which is generally the
case, are considered and addressed using the concept of distributionally robust optimization (DRO) to develop solutions that guarantee safety or the successful completion of the
task despite the lack of knowledge of the underlying distribution.
Throughout, examples are provided to emphasize and clarify core concepts, and simulations and physical experiments are performed to demonstrate the efficacy of the developed
solutions
Global Characteristics of Large-scale Traveling Ionospheric Disturbances During Geomagnetic Storms
No full textThis dissertation presents an investigation of the vertical and longitudinal behavior of Large
Scale Traveling Ionospheric Disturbances (LSTIDs). LSTIDs are an ionospheric signature of
perturbations propagating in the neutral atmosphere which are generated, for example, due
to the change in energy deposition rate within the auroral zone during a geomagnetic storm.
Geomagnetic storms are natural phenomena that arise from the interaction between the solar
wind and Earth’s magnetic field. Among the various disturbances occurring as a result of this
interaction, LSTIDs have garnered significant attention in recent years due to their potential
to disrupt communication and navigation systems. LSTIDs are wave-like perturbations in
the ionosphere, a layer of Earth’s atmosphere where particles are largely ionized, which
cause variations in plasma density, temperature, and drift velocity. The electron density
perturbations in particular alter the index of refraction of the ionosphere, affecting the
integrity of radio waves propagating through the region. The investigation of LSTIDs during
geomagnetic storms is of paramount importance, as it offers insights into the behavior of
the ionosphere under extreme conditions, and it may help mitigate potential technological
vulnerabilities.
The central objective is to comprehensively analyze the global distribution of these ionospheric
disturbances and determine the impact of season, onset time, and the local time of geomagnetic
storm onset on LSTID characteristics. To achieve this, a novel combination of the Global
Ionosphere Thermosphere Model (GITM) and SAMI3 is Also a Model of the Ionosphere
(SAMI3) is used to model LSTID behavior throughout a variety of synthetic geomagnetic
storms. Geophysical indices are generated which represent a geomagnetic storm, allowing
control of the exact date and time of storm onset. The response of ionosphere-thermosphere
system to geomagnetic storms at solstices, equinoxes, and across several onset times are
compared. This isolates the effect of the offset between the geographic and geomagnetic poles.
Results focus on how the differing patterns of Joule heating influence the LSTIDs produced
across the range of storms modeled.
Additionally, the models facilitate the view of the full altitude range of the ionosphere (unlike
most measurements which are attributed to a single altitude), simulating measurements in
regions where ground-based measurements are not available (e.g. over the oceans), and allow
the investigation into the time-evolution of satellite point-measurements. These models are
used to illustrate how satellites (DMSP) density measurements can be used to characterize
the behavior of LSTIDs where ground-based receivers cannot be placed. The validity of the
analysis of simulated and in-situ data are shown from a selected geomagnetic storm.
This research contributes to the broader field of aeronomy by advancing the understanding of
the distribution of LSTIDs and will give insight into utilizing novel observational techniques
to further the understanding of the behavior of LSTIDs
The Topos of Unhomeliness: Representations of Home and Homeland in Chinese American and Tibetan Chinese Literature
No full textThis dissertation studies the representations of home and homeland in the literary works of some
major writers in Chinese American and Tibetan Chinese literature. The chosen writers include
Amy Tan, Frank Chin, Ha Jin, Yan Geling, Zhaxi Dawa, Alai, Pema Tseden, and Takbum Gyel.
By examining their fictional and non-fictional works, this dissertation explores an interesting
phenomenon: even as the writers are in their homes, they are (un)consciously haunted by a sense
of homelessness, which has formed a major theme in their literary works. According to the
current scholarship of Asian American and Tibetan Chinese literature, the anxiety over home for
Chinese American and Tibetan Chinese writers comes from different sources. While for the
former is rooted in their ancestral home, for the latter is derived from the loss of traditional
home. This dissertation argues that the anxiety over home for both ethnic groups is much more
complicated than it is recognized. For the Chinese American writers, the anxiety figures in
literary representations of Tan’s disharmonious home, Chin’s estranged home, Ha Jin’s
transitional homeland, and Yan’s dualistic homeland. In those representations, the home loses its
homeliness in the conflict between the mother and daughter, the dispute between the father and
son, the rootless movement from filiation to affiliation, and the fruitless search for an ideal home.
For the chosen Tibetan Chinese authors, the anxiety is represented as Zhaxi Dawa’s hybrid
homeland, Alai’s universal homeland, Pema Tseden’s incompatible home, and Takbum Gyel’s
transitional homeland. In those writers’ works, the home loses its simplicity, uniqueness,
harmony, and authenticity as a result of the hybridity of primitivity and modernity, the merge
into modern history, the confrontation between tradition and modernity, and the transition from
the old era to the new one. By analyzing the images of home and homeland in the two ethnic
minority groups’ literature, the dissertation argues that the home plays different roles in the two
group of writers’ writing careers. For Chinese American writers, it is like a haunting ghost,
which stimulates both love and hate; for Tibetan Chinese writers, it is a changing muse, whose
transformations make it difficult for them to show their love for it. The difference comes from
the different nature of their identities and structures of feelings. Each group’s identity consists of
two parts: one natural and the other national. The dominant variant and the recessive variant of
their identities are opposite. The opposite determinants of the dominant and the recessive
variants are responsible for different representations of home and homeland in the Chinese
American and Tibetan Chinese writers’ works