VictorJuiz/thesis huggingface dataset:
Integrated Polymer Microfluidic-Electronic Sensors and Actuators

Though microfluidic and BioMEMS devices have been active areas of research since the late 1990s, commercial success of diagnostic tools making use of these technologies has been limited, especially with regard to complex “micro-total analysis systems” with integrated fluid control and sample preparation. The incompatibility of current prototyping technology (PDMS soft lithography) used during the discovery phase with large-scale industrial production and the difficulty of integrating electronic sensing and fluid control with PDMS devices contribute to this problem by requiring substantial redesign of microfluidic devices from prototype to manufacturable product. Therefore, there is a need for a lab-scale prototyping method that is compatible with manufacturing-friendly materials and which allows for simple integration of electronic components./nI will describe such a method based on hot embossing of thermoplastics and propose modifications to this method which allow for simultaneous patterning of microfluidic channels and integration of electrodes with a variety of geometries. This method involves minimal specialized equipment and is similar in complexity to the fabrication of PDMS devices. Furthermore, I will describe applications of this manufacturing technology to impedance cytometry and electrolysis-driven pumping./nEfforts to increase the complexity and decrease the footprint of microfluidic devices also require novel strategies for on-chip sensing and actuation. To that end, I will also describe two strategies for such compact active devices. The first is a pump powered by chemical propellant and fabricated using high-resolution 3D printing, which has been applied to oral vaccine delivery. The second is an electrically-actuated magnetic particle sorter which makes use of the inverse magnetostrictive effect in a multiferroic heterostructure to achieve local control of particle motion without an external magnetic field./nTaken together, the work described in this dissertation is intended to advance the potential of integrated microfluidic systems to function without the requirement of an extensive external infrastructure including off-chip pumps and microscopes, and to ease the transition of microfluidic devices out of the lab by incorporating some design-for-manufacturing ideas into the early stages of the development of such devices.

Advisor: Liepmann, Dorian
Mechanisms of Size Control in Pipid Frogs

Size is a fundamental feature of biology that affects physiology at all levels, from the organism to organs and tissues to cells and subcellular structures. How size is determined at these different levels, and how biological structures scale to fit together and function properly are important open questions. Historically, amphibian systems have been extremely valuable to describe scaling phenomena, as they occupy some of the extremes in biological size and are amenable to manipulations that alter genome and cell size. More recently, the application of biochemical, biophysical, and embryological techniques to amphibians has provided insight into the molecular mechanisms underlying scaling of subcellular structures to cell size, as well as how perturbation of normal size scaling impacts other aspects of cell and organism physiology. This thesis is comprised of three projects which examine mechanisms of size scaling in Pipid frogs at the subcellular, cellular, and organismal levels. We find that molecular mechanisms for spindle size scaling in eggs of the small frog Hymenochirus boettgeri are not conserved with those of Xenopus species. Instead, a novel mechanism operates involving post-translational modification of microtubule depolymerizing motor protein kif2a to modulate spindle size. We also characterize size scaling in viable Xenopus laevis/ Xenopus tropicalis hybrids and use this system to establish a novel screening method for candidate genes involved in size control. Finally, we characterize size scaling in the rare dodecaploid Xenopus longipes to examine how genome size impacts cell size and other traits such as developmental rate. The well-documented correlation between genome size and cell size is conserved in somatic cells but not in early development, which proceeds more slowly in Xenopus longipes than in Xenopus laevis, thus highlighting an important correlation between genome size and developmental rate.

Advisor: Heald, Rebecca
The Design of Dynamic Neural Networks for Efficient Learning and Inference

Intelligent systems with computer vision capabilities are poised to revolutionize social interaction, entertainment, healthcare, and work automation. Recent progress in computer vision research, especially with deep learning methods, is largely driven by immense datasets, complex models, and billions of parameters. However, real-world applications often neither have access to large scale datasets nor can afford expensive data labeling and computation overhead. Furthermore, we live in a dynamic world, which requires machine learning models to handle changing data distributions and novel prediction tasks. When using learning techniques in actual systems, we still face significant hurdles coming from the scarcity of data and labels, limited computation, and never-ending varying prediction scenarios./nThe focus of this thesis is the design of dynamic neural networks and its application to efficient learning (e.g., few-shot learning, semi-supervised learning) and inference. Dynamic networks adapt the model parameters and structures as a function of the input to leverage test-time information. For example, we introduce the design of dynamic neural architectures that can scale their computational complexity as a function of the input. To achieve small improvements in prediction accuracy, deep neural networks are rapidly increasing in depth and computational complexity. Also, the same amount of computation is applied regardless of the input. However, many inputs can reduce the level of computation required to render an accurate prediction. In Part I, we describe a range of dynamic models such as SkipNet and DeepMoE, which adjust the network depths on a per-input basis without reducing the prediction accuracy. In Part II, we describe the usage of dynamic neural networks for sample efficient learning. We propose dynamic weight generation using a task-aware meta learner and its application to a few-shot learning setting. We find that adapting the network parameters at prediction time improves model generalization.

Advisor: Gonzalez, Joseph
Darrell, Trevor
The Authoritarian Foundations of the Rule of Law: Organizational Autonomy, Pluralism and Civil Society in Spain and Mexico

The dominant theoretical view about the social and political foundations of the rule of law is a liberal reading of the pluralist tradition in sociology. From this perspective, the combination of democracy, capitalism, and a strong civil society produce the rule of law. By extension, authoritarianism is viewed as antithetical to the rule of law, and the institutional legacies it leaves behind make it more difficult for countries to build autonomous, competent, and trust-worthy judicial systems in the post-authoritarian period. In this work I argue that the cases of twentieth century Spain and Mexico are anomalies for this paradigm. When Francisco Franco took power in Spain in 1939 he built one of the harshest authoritarian regimes of the twentieth century. It was precisely the strong authoritarian hold he secured over the judicial system combined with a weak civil society that established the foundations for the rule of law in post-authoritarian Spain. In contrast, the far more pluralist regime of the PRI in Mexico, built around a patronage system, along with a strong and litigious civil society undermined Mexico’s ability to build judicial state capacity in the post-authoritarian stage. These findings prompt us to reconsider the relationship between authoritarianism and the rule of law and compel us to remember the modernizing effects authoritarianism can have, with implications for cases beyond Spain and Mexico.

Advisor: Riley, Dylan J.
Mora, G. Cristina
Drug Monitoring with Wearable Sweat Sensors

Wearable sensors have been very popular among us to monitor our physical wellness, and they are potentially important for health monitoring with implications toward preventive care and clinical treatment. On the market, noninvasive wearables can be used to track external metrics such as heart rate and ECG signal. However, they fail to inform users about elusive biomarkers at the molecular level, which can potentially provide more insight into a person’s health situation. Traditionally, accessing bio-molecular information requires collecting blood or urine samples with invasive extraction or logistic complications. In this regard, sweat stands out as a great candidate because of its noninvasive property and abundance in biomolecules, such as electrolytes, metabolites, xenobiotic molecules, and heavy metals. Our group has demonstrated noninvasive and multiplexed sensing of biomolecules by interfacing flexible printed circuit boards and electrode arrays. The advantage of this kind of sensor is that it enables real-time monitoring, requires small sample volume, and detects multiple biomolecules simultaneously. The sweat monitoring device allows us to potentially monitor our health statuses and screen diseases. However, a challenge that is equally important to screening diseases is to have an effective treatment that typically involves drug intake. So the question that remains is whether we can monitor drug molecules using a wearable sweat sensor? After an introduction in Chapter 1, we will explore this possibility in Chapter 2. A methylxanthine drug, caffeine, is selected to validate the sensor’s functionalities. Chapter 3 seeks the sensor’s potential applications in clinical settings. The focus is on levodopa, which is typically used for treating patients with Parkinson’s disease. In Chapter 4, the sensing platform is reconfigured for secondhand smoke detection, which can potentially be used by a broader population. In summary, we have demonstrated wearable sweat sensors capable of monitoring selected molecules related to drugs. This work leverages a wearable sweat sensor towards noninvasive and continuous point-of-care drug monitoring and management.

Advisor: Javey, Ali
Mandatory Short Disclosures: An Information Story

Requiring short sellers to disclose their positions may discourage them from participating in the market, thus harming price efficiency (“constraint effect”). However, it may also provide a new source of value-relevant information to the market, thus improving price efficiency (“information effect”). The two effects counteract each other, rendering it difficult to empirically capture each effect distinctly. While prior literature has provided evidence of the constraint effect, it has left the information effect relatively unexplored. I identify a setting during which the information effect dominates, namely the earnings announcement setting, and document the implications of the information effect: information asymmetry and uncertainty decline around the announcement, pre-announcement information acquisition is greater, and earnings news is impounded more efficiently following its release. I study EU regulatory changes in a staggered difference-in-differences design. The empirical findings in this paper provide additional insights for the ongoing debate on short disclosure regulation in the US, providing credence to the argument of its advocates that mandatory short disclosures would provide valuable information.

Advisor: Patatoukas, Panos
Drumball: Digital drum talk as a medium to promote multimodal literacy and socio-emotional development of children

Recently, research efforts to close the achievement gap have highlighted the importance of understanding children’s experiences in the early years, how they come to learn about literacy practices and about their identities and positions in the world, in order to identify and address the challenges they soon may be facing. As the educational community continues to seek effective approaches to pedagogy and curriculum that will curtail the trend of a widening literacy gap in the future, researchers and practitioners look to the careful study of small-scale interventions in their target settings as a viable path for improving teaching and learning practices through the refined articulation of principles and processes that underpin their activity. Through that understanding, the design of learning ecologies can be approached by leveraging the potential in those elements of interventions that show promise in increasing the individual achievement and social participation of children, especially those most underserved by the prevalent cultural approach to learning in our schools. Using cultural historical activity theory as a lens, this design-based study instituted an Urban Griots Playground intervention and a researcher developed Drumball-Alphariddims digital platform as an embodied rhythmic-based learning system to stimulate children’s literacy development and multimodal meaning production through joint child-parent activity. Qualitative data on five 3 – 6 year-old participants and their parents were collected in the form of pre- and post-tests, interviews, surveys, observations, audio/video recordings, and focus group discussions.  Key findings from this study were that the intervention model encouraged the children’s exploration of literacy behaviors through embodied learning, fostering emotional understanding and key social participation dispositions, while providing parents’ with tools for evaluation and positioning them as social partners and enablers of their child’s learning. The significance of this study is that it provides children, parents and educators with a culturally-grounded approach to early literacy experiences that combines rhythmic communication with new tangible and wearable media technologies.

Advisor: Mahiri, Jabari
Original Echoes: Poetic Subjectivity and Translation between Italy, France, and the United States

Original Echoes: Poetic Subjectivity and Translation between Italy, France, and the United States argues for a reconfiguration of twentieth century poetics to include the crucial interventions of its translators of poetry. Triangulating between Italian, French, and English in the 1940s, the dissertation takes as case studies Fernanda Pivano’s 1943 Italian translation of Spoon River Anthology by Edgar Lee Masters, and Louise Varèse’s 1946 English translation of Illuminations by Arthur Rimbaud. Through close readings of both source text and translation, Original Echoes reveals how these translations productively shift from their source texts, reconstructing how they made cultural, aesthetic, and political interventions in their receiving cultures—Italy under fascism, and the United States post-WWII. By drawing on Translation Studies, theories of comparative lyric, as well as feminist critiques that seek to redefine the hierarchical relation between source and translated texts, the dissertation theorizes the lasting intervention of these translators as proceeding from a paradoxical emphasis on fidelity, self-effacement and equivalence./nThe four chapters of the dissertation alternate between chapters discussing a source text and chapters analyzing its translation. In Chapter One (“Spoon River Anthology: Lyric Address and Fatal Birth”) I examine the innovative form of the epitaph-monologues in Edgar Lee Masters’s Spoon River Anthology, and how it critiques lyric address, while showing that the collection’s representation of crises of women’s health in particular exposes the limits to this critique. In Chapter Two (“Talento disobbediente: Fernanda Pivano’s Spoon River”) I argue that Pivano’s translation of Spoon River, in collaboration with poet-editor Cesare Pavese, redirects Spoon River’s poetic innovations by giving the collection a new life as an antifascist text in Italy. In Chapter Three (“Trouver une langue: English in Rimbaud’s Illuminations”) I turn to Illuminations, Arthur Rimbaud’s collection of prose poems from 1886, and read his use of English as it moves beyond a nationalist critique to reveal the otherness inherent in poetic language. And lastly, in Chapter Four (“Activating Translation: Louise Varèse’s Illuminations”) I reconsider Varèse’s much-lauded “accuracy” as a translator of Rimbaud as a form of close translation that renders the strangeness of Rimbaud’s language while retaining remnants of its own belatedness as a translation. The Conclusion briefly considers the legacy of these translations.

Advisor: Spackman, Barbara G
Thermal Dust: An Ultrasonically-Powered Implantable Temperature Sensor

Temperature measurements find use in clinical settings for the monitoring of various disease states, and the monitoring of deep tissue temperature patterns in both space and time can provide valuable information about tissue health. Unfortunately, current clinical methods are not suitable for continuous monitoring of temperature measurements. Recently, acoustically-powered implants have been emerging as a method to enable small medical devices that can be implanted deep in the tissue. In this thesis, we demonstrated the development of two versions of implantable temperature sensors that we call thermal dust. Thermal dust motes are ultrasonically-powered, ultrasonically-communicating sensors, and were demonstrated as both a passive sensor mote and an active sensor mote. We designed passive thermal dust motes using only commercial off-the-shelf (COTS) components, and these sensors were fully sub-millimeter in all of their dimensions. We showed experimentally that passive thermal dust motes were able to encode temperature data using analog amplitudebackscatter modulation. Active thermal dust motes consist of a custom integrated circuit (IC) that we designed in a TSMC 0.18 μm biCMOS process. We experimentally demonstrated the operation of our thermal dust chip in the physiologically-relevant temperature range of 30 – 50°C as well as an elevated temperature range of 60 – 80°C to demonstrate the versatility of our device. Finally, we showed that the binary duty cycle modulation of the backscatter waveform envelope is a feasible method to encode temperature data, and we demonstrated fully wireless operation of an active thermal dust device.

Advisor: Maharbiz, Michel M
Nonlinear Spectroscopy in the Extreme Ultraviolet: Probing Ultrafast Electronic Dynamics in Atoms, Molecules, and Solids with Attosecond Pulses

Nonlinear spectroscopic techniques with attosecond extreme ultraviolet (XUV) pulses produced by high harmonic generation promise to enable the study of ultrafast processes driven by electronic dynamics. Although nonlinear spectroscopies are regularly utilized to probe chemical dynamics driven by nuclear motion, the extension of these techniques to electronic dynamics has been limited by the low flux of attosecond light sources. In this dissertation, nonlinear techniques that incorporate subfemtosecond XUV pulses and few-cycle near infrared (NIR) pulses generate transient higher-order signals from electronic states in gas-phase and solid-state samples. Manipulation of the pulse sequence, wavevector, and spectrum permits selective measurements of dynamic processes with exceptional temporal and spectral resolution. This dissertation details the development and application of attosecond nonlinear spectroscopies. Attosecond transient absorption experiments at the iodine N4,5 edge of ICl demonstrate that the molecular environment dramatically impacts core-excited state lifetimes. To probe these electron correlation-driven dynamics more selectively, an attosecond wave-mixing spectroscopy has been developed. Capitalizing on phase matching to isolate higher order signals, wave-mixing experiments on the 1snp Rydberg and light-induced states in helium reveal few-femtosecond delays in higher order signal generation due to the accumulation of a phase grating. Further experiments on this system show that wave-mixing signals from light-induced states can be amplified using self-heterodyne detection schemes. Moreover, these attosecond wave-mixing techniques are employed to measure the lifetimes of states that decay via electron correlation. Despite pronounced quantum beating, lifetimes obtained for the (2P1/2)nd autoionizing states of krypton compare favorably with linewidth measurements. In solid-state NaCl, attosecond wave-mixing techniques uncover several additional core-excitons that underlie the absorption features of Na+ L2,3 edge, and report ultrafast bright and dark state dynamics suggestive of the complex environment. Designed to differentiate distinct contributions to higher order emission signals, an XUV multidimensional spectroscopy based on a pulse shaping apparatus effectively eliminates quantum beat signatures in a proof of principle experiment in argon./nThese results illustrate the potential of attosecond nonlinear spectroscopies to elucidate dynamics driven by electron correlation in diverse systems with unprecedented selectivity. Future work will translate these nonlinear techniques to the chemically-significant carbon K-edge, where they will provide insight into the electronic dynamics foundational to chemical reactions.

Advisor: Leone, Stephen R
Neumark, Daniel M
Merging Molecular, Materials, and Biological Design Elements in Catalysts for Small Molecule Activation and Conversion

Understanding and manipulating transformations of CO2, O2, H2O, NO3–, CH4, and N2 is crucial for establishing sustainable energy cycles, and using inputs such as electricity or light allows coupling of these reactions to renewable sources. Developing platforms that can activate these molecules is a continuous challenge and must be approached from many directions. As such, we take inspiration from homogeneous molecular, heterogeneous materials, and biological enzyme catalysis to create more effective platforms. This dissertation describes this general approach and then focuses on a supramolecular strategy that integrates the structural tunability of molecular porphyrin catalysts into a rigid and porous architecture that benefits from a materials-inspired high surface area. This platform is widely applicable, showing various improvements in the catalysis of CO2, O2, and H2O reduction. We also present a bio-molecular platform that combines a synthetic porphyrin catalyst with bio-inspired additives that can function as electron and proton mediators resulting in improved CO2 reduction. Overall, our general strategy for blurring the lines between molecular, materials, and biological fields of catalysis has proven fruitful and aids in the rational design of more optimized systems.

Advisor: Chang, Christopher J