VictorJuiz/thesis huggingface dataset:
Non-covalent Interactions in the Gas Phase: Infrared Spectroscopy and Nanocalorimetry of Ion-Biomolecule Complexes

In this dissertation, experiments investigating the effects of non-covalent interactions on the structure and reactivity of gas-phase, ion-containing clusters, including ion-amino acid and ion-water complexes, are presented and discussed. Ions generated using electrospray ionization and analyzed using Fourier transform ion cyclotron resonance mass spectrometers at the University of California, Berkeley, and the FOM Institute for Plasma Physics Rijnhuizen in Nieuwegein, The Netherlands, are investigated using infrared photodissociation/infrared multiple photon dissociation (IRPD/IRMPD) spectroscopy, collision-induced dissociation, and electron capture dissociation (ECD). Using ion nanocalorimetry, the effect of varying the potential which controls the kinetic energy of the thermally generated electrons used for ECD experiments is determined to be minimal under typical experimental conditions. The results indicate that only a small population of electrons with near zero velocity relative to the trapped hydrated ions are captured and result in the observed ECD products. IRMPD spectra of proton-bound heterodimers containing valine and basic amines indicate that the structure of the heterodimer changes with increasing basicity of the amine suggesting that the structure of an amino acid in a proton-bound dimer may be different than in isolation which breaks an assumption made in the determination of gas-phase basicities using the kinetic method. IRMPD spectra of ion-amino acid complexes reported here reveal the effects of gas-phase acidity, ion polarity/charge state and ion size on the relative zwitterionic stability of the amino acids. The coordination numbers (CN) of hydrated divalent transition metals are determined using IRPD spectroscopy and photodissociation kinetics measurements. The CN of Cu2+ is lower than the other metal ions (CN = 4) due to Jahn-Teller effects brought about by the d9 electronic configuration of the ion. IRPD spectra of SO42- with up to 80 water molecules attached indicate that the structure induced by the dianion dominates over the intrinsic water-water interactions for clusters with up to 43 water molecules, well beyond the first solvation shell. The roles of ion charge state and cluster size in the structure of gas-phase "nanodrops" are investigated for the largest mass-selected ionic clusters for which IRPD spectra have been reported. Effects of ion charge state are observed for nanodrops containing up to ∼250 water molecules in contrast with recent reports that only the first solvation shell is affected by ions in aqueous solution.

Advisor: Williams, Evan
Protein Delivery to Eukaryotic Cells by Engineered Bacteria

Synthetic biologists engineer genetic circuits for applications ranging from biosynthesis to biotherapeutics. Although the application of engineering strategies such as standardization, abstraction, and modularity has long been highlighted as the path to designing complex biological systems, early work generally relied on an ad hoc strategy, limiting applications to relatively simple systems. More recently, several groups have explicitly applied modular design to the development of biosynthetic pathways, biological computation, and increasingly sophisticated logic functions. However, connection of distinct functions to create a useful system-level behavior remains a key challenge. We assessed a possibility and limitation of a modular design when engineering a complex biological system./nBy applying a modular design, we engineered E. coli to deliver macromolecules to the cytoplasm of cancer cells in vitro. Fabrication, testing, composition, and troubleshooting of five functional modules produced an efficient system capable of delivering proteins to over 80 % of targeted cancer cells. The modular design strategy enabled facile system modification for both troubleshooting and optimization. These devices were then mixed and matched to build a new type of delivery device that enabled E. coli to escape from the vacuole and secrete payloads. The delivery system was then further modified to deliver payloads to other eukaryotic organisms./nSuccessful application of modular design to the delivery system demonstrates that abstraction is a simple yet powerful tool for making the design of complex biological systems tractable. We expect that continued refinement of modular design, including incorporation of relevant quantitative information, will enable construction of increasingly complex systems. We envision that the bacterial delivery system developed here may itself become a high level module that can be incorporated into the design of more complex systems, such as a therapeutic bacterium delivering cancer-cell specific microRNA.

Advisor: Anderson, John C
Using Mobile Technology and Social Networking to Crowdsource Citizen Science

This dissertation explores the application of computer science methodologies, techniques, and technologies to citizen science. Citizen science can be broadly defined as scientific research performed in part or in whole by volunteers who are not professional scientists. Such projects are increasingly making use of mobile and Internet technologies and social networking systems to collect or categorize data, and to coordinate efforts with other participants./nThe dissertation focuses on observations and experiences from the design, deployment, and testing of a citizen science project, Creek Watch. Creek Watch is a collaboration between an HCI research group and a government agency. The project allows anyone with an iPhone to submit photos and observations of their local waterways to authorities who use the data for water management, environmental programs, and cleanup events./nThe first version of Creek Watch was designed by a user-centered iterative design method, in collaboration with scientists who need data on waterways. As a result, the data collected by Creek Watch is useful to scientists and water authorities, while the App is usable by untrained novices. Users of Creek Watch submit reports on their local creek, stream, or other water body that include simple observations about water level, water flow rate, and trash. Observations are automatically time stamped and GPS tagged. Reports are submitted to a database at creekwatch.org, where scientists and members of the public alike can view reports and download data./nThe deployment of Creek Watch provided several lessons in the launch of an international citizen science mobile App. Subsequent versions of the iPhone App solved emergent problems with data quality by providing international translations, an instructional walk-through, and a confirmation screen for first-time submissions./nThis dissertation further examines how social networks can be used for recruitment and promotion of a crowdsourced citizen science project and compares this recruiting method to the use of traditional media channels. Results are presented from a series of campaigns to promote Creek Watch, including a press release with news pickups, a participation campaign through local organizations, and a social networking campaign through Facebook and Twitter. This dissertation also presents results from the trial of a feature that allows users to post Creek Watch reports automatically to Facebook or Twitter./nSocial networking was a worthwhile avenue for increasing awareness of the project, which increased the conversion rate from browsers to participants. The Facebook and Twitter campaign increased participation and was a better recruitment strategy than the participation campaign. However, targeting existing communities resulted in the largest increase in data submissions.

Advisor: Hearst, Marti
Hellerstein, Joe
Individual differences in white matter integrity: Linking brain structure to cognition in children and adults

For disparate brain regions to communicate efficiently action potentials must be transmitted relatively long distances along myelinated axons, which make up the brain's "white matter". These connections are fundamental for the generation of complex cognition. A single cortical region is not sufficient--the human brain must work as a network, with the billions of neurons interacting together to perform the necessary computations. In my graduate work, presented in this dissertation, I sought to explain the variability in cognitive behavior with individual differences in white matter microstructure. The overarching goal was to further our understanding of the mechanisms through which structural connections in the brain underlie complex cognition in children and adults./nI used diffusion tensor imaging, a type of magnetic resonance imaging that is sensitive to white matter microstructure, to quantify in vivo the maturation of white matter in children and adults. I first motivate the need to study the individual differences in white matter integrity and their predictive value on cognitive behavior in chapter one. I then describe four experiments that investigate various aspects of this connection. In chapter two, I first describe the age related changes in brain and behavior through childhood and adolescence, and then use longitudinal data to highlight the additional explanatory power of how within-person measures of change (in brain and cognitive ability) over time are linked. In chapter three, I demonstrate the mediation of the relationship between white matter integrity (WMI) and reasoning ability by cognitive processing speed in typically developing children./nIn chapter four, I show the WMI differences between two groups of adults who have experienced different perceptual environments through development (synesthetes and non-synesthetes) and demonstrate a correlation between vividness of visual imagery and the WMI of the synesthetic brain. Finally, in chapter five, I explain the effects of short term cognitive training on WMI . After only three months of undergoing an intensive reasoning training program we saw evidence of cellular reorganization in the white matter of healthy young adults. I conclude by summarizing the major contributions of the work in this dissertation and discuss possible future directions based on the results of my graduate research.

Advisor: Bunge, Silvia A
Investigating the Role of Force and Stiffness in Controlling Cell Behavior

Forces and the mechanical properties surrounding eukaryotic cells have been increasingly shown to play crucial roles in modulating biological functions, from healthy tissue development to disease progression. This work focuses on three aspects of cellular responses to their mechanical microenvironment: stiffness sensing, force regulation, and the effect of cancer progression on tissue architecture and elasticity. To make quantitative measurements of cell properties, I developed a novel technology based on atomic force microscopy (AFM) that is capable of dynamically controlling microenvironmental stiffness, as well as measuring forces and displacements. I first observed that cells nearly instantly change their contraction in response to step changes in stiffness (Chapter 2). I then determined that this process requires a mechanical equilibrium that balances contraction of the viscoelastic cytoskeleton with deformation of the extracellular matrix. This seconds-timescale equilibration provides a lower bound to the rate of whole-cell scale stiffness sensing (Chapter 3)./nExtracellular matrix stiffness has been identified as a key driver of tumorigenesis, but elucidating the link between tissue architecture and elasticity has remained experimentally difficult. Using AFM, I observed a near 2-fold stiffening of pre-malignant breast epithelial spherical structures, called acini, which are responsible for milk production, as well as are the initial site of many breast cancer cases. Further, the specific apparent microenvironmental stiffness for an epithelial cell within this acinar structure was calculated using 3D computational modeling, revealing a marked difference in compliance independent of extracellular matrix changes (Chapter 4)./nA widely cited concept in cellular mechanosensing to explain the response of cells to changes in their mechanical microenvironment is "tensional homeostasis", whereby adherent cells will actively respond to compression or extension by maintaining some previously established tension. However, no experiments have yet directly shown this behavior at the single cell level. Using a combination of protein patterning and AFM, I provide the first evidence of this homeostatic behavior. Notably, I found that cells do not maintain an absolute setpoint, but rather work to counteract force changes at a slow rate, beyond which force will freely change, a process I term tensional buffering. In addition, after rapid loading, cells will work to maintain their new level of tension, not returning to a previous setpoint (Chapter 5)./nUltimately, these advances further our understanding of the role of mechanics in both healthy and diseased cellular processes, laying the groundwork for tissue engineering approaches for growing healthy tissues or therapeutic targets for a new array of hard to treat diseases.

Advisor: Fletcher, Daniel A
Essays in Methodology

Academic contributions in any discipline are only as convincing as the methods used to establish them. This dissertation highlights two methodological issues in economics---one in experimental economics and one in applied econometrics---and argues for increased caution in both the design and the interpretation of empirical studies. Within experimental economics the Becker-DeGroot-Marschak (BDM) mechanism is widely used to elicit the valuations of experimental subjects. Although it is theoretically incentive compatible, empirical evidence suggests that elicitations are affected by the distribution from which the random price is drawn. The second chapter presents a novel, within-subjects data of sequential BDM rounds with varied distributions to directly investigate and characterize distributional dependence. When analyzing data collected outside of the realm of randomized experiments (in the laboratory or otherwise), fixed effects are frequently used to ``control for'' the potential influence of observed factors on an outcome variable of interest. The third chapter discusses potential pitfalls in the use and interpretation of fixed effects. The goal of each of these chapters is to offer positive suggestions for more careful future research through marginal improvements in empirical design and practice.

Advisor: Malmendier, Ulrike
The Image of Truth: Truth-Practices and Portable Technology in Contemporary Italian Video-Journalism

In this dissertation I examine the forms and possibilities of truth-speaking in contemporary Italian news and media industry. I ask the following questions: 1) What does an Italian contemporary journalist need to do in order to be acknowledged as a truth-teller? 2) How does technological innovation, and in particular portable video-technology, influence self-reflexivity? 3) What kind of relation to the political present does truth-telling enable?/nI assume Italy's news and media industry as a "case-study" rather than as a self-enclosed field because my focus is on a problem rather than on a "culture". The approach followed in this dissertation is thus a conceptual one: rather than highlighting the Italian cultural specificity, I seek to conceptually articulate problems in news and media that, while more manifest in Italy, belong to contemporary news and media industry per se. Approaching Italian journalism as a "case-study" enables the author to address a more general topic: the transformation of contemporary forms of self-reflexivity in the sway of technological and political change, and, in particular, of that quintessential form of self-reflexivity that is truth-speaking. Since I adopt a conceptual approach, I explore, where I find it necessary, "cases" seemingly "far away from the field", such as the semiotics of all-news channel Aljazeera's website (Chapter II); the ethics of BBC's treatment of the Libyan revolution (Chapter III); or the use of portable media in the Libyan revolution itself (Chapter IV). Every chapter focuses on a specific aspect of truth-speaking: its relation to self-reflexivity, to economy, to technology, and to aesthetics.

Advisor: Rabinow, Paul
Estimation of Complex Generalized Linear Mixed Models for Measurement and Growth

Maximum likelihood (ML) estimation of generalized linear mixed models (GLMMs) is technically challenging because of the intractable likelihoods that involve high dimensional integrations over random effects. The problem is magnified when the random effects have a crossed design and thus the data cannot be reduced to small independent clusters. A variety of methods have been developed for approximating the intractable likelihood functions, but there seems no method yet that is both computationally efficient and accurate in a wide range of situations. In this dissertation, I consider new estimation methods and applications of complex GLMMs for measurement and growth. The dissertation consists of three papers,/n1) Variational maximization-maximization (MM) algorithm,/n2) Monte Carlo local likelihood (MCLL) estimation,/nand 3) Autoregressive item response theory (IRT) growth model for longitudinal item analysis./nIn the first and second papers, I develop two ML methods for estimating GLMMs with crossed random effects. The variational MM algorithm is a modified expectation-maximization (EM) algorithm where a variational density is introduced in the expectation (E) step to approximate the true posterior density of the random effects given the data. The E-step is replaced by another maximization step that minimizes the Kullback-Leibler (KL) divergence between the posterior and the variational density, or equivalently, maximizes the lower bound of the log-likelihood with respect to the variational distribution. The MCLL algorithm uses the posterior samples of model parameters obtained from Markov chain Monte Carlo (MCMC) for likelihood inference. The posterior density is estimated by local likelihood density estimation and the likelihood function is approximated up to a constant by the local likelihood density estimate of the posterior divided by the prior. The performance of these new algorithms is evaluated using simulation and empirical studies and compared with other ML and Bayesian estimators. In the third paper, a new autoregressive IRT growth model is proposed to take into account serial correlations among responses to the same items over time. The consequences of ignoring serial dependence and the initial conditions problem are investigated using simulations. The new model is applied to longitudinal data of Korean students' self-esteem.

Advisor: Rabe-Hesketh, Sophia
Buckling and Topological Defects in Graphene and Carbon Nanotubes

Graphene is the strongest material ever discovered and has an extremely high Young's modulus (~ 1 GPa). Although stretching the sp2 covalent bonds between carbon atoms is very difficult, significant deflections do develop in graphene membranes. In fact, thermal rippling naturally emerges in graphene at any finite temperature. Moreover, the topological defects mediating plastic deformation often cause out-of-plane crumpling, an effective way to reduce the total elastic energy of the topological defect. It is even possible to design specific stress states to produce periodic wrinkles in graphene with adjustable wave lengths./nThis work aims to understand how buckling influences the elastic and plastic behavior of graphene-based nanostructures. While the elastic moduli may be straightforwardly computed using structure optimization techniques with applied test stresses, it is a nontrivial task to obtain elastic properties at any specific temperature. Further, linear elastic theories are not able to describe large buckling because the second order nonlinear terms in the definition of the Lagrangian finite strain tensor cannot be neglected. In addition, the existence of topological defects and constraints need to be properly treated. Finally, buckling and defects of a curved surface such as a nanotube is even more complicated and poses other intriguing challenges./nTo proceed, we employ Monte Carlo techniques to obtain fundamental elastic properties of graphene at desired temperatures, which supplies useful inputs for a nonlinear continuum model for graphene. This model not only takes into account, in a suitable manner, both large out-of-plane buckling and interactions among edge dislocations with periodic boundary conditions, but also serves as a handy tool for simulating nanoindentation experiments and the controlled wrinkling of graphene. At last, we focus on the Stone-Wales defect mediated plasticity of CNTs. Specifically, a kinetic Monte Carlo framework is designed to model the defect dynamics over a long time scale. We find that in large nanotubes, a chain of closely packed dislocations (called a "dislocation worm") may have less buckling and lower formation energy than the conventional dislocation glide under high tensile stresses.

Advisor: Chrzan, Daryl C
Essays in Financial Economics

This dissertation is comprised of two chapters, each of which contributes to the field of financial economics, particularly in the areas of behavioral and household finance./n"Corporate News, Asset Prices, and the Media" examines investor reaction to stale information using a novel data set containing a time-stamped transcript of the financial news network CNBC. I measure changes in stock price and trading volume at the precise time that a company is mentioned on CNBC in the 24 hours following a corporate news event, and find strong evidence that some investors react to stale news. There is a significant increase in stock price at the precise time that a company is mentioned on CNBC following a positive news event. Surprisingly, there is also a significant increase in stock price at the precise time that a company is mentioned on CNBC following a negative news event. This puzzle is not explained using observable differences between positive and negative news events or their subsequent mentions. Evidence using cross-sectional variation in the number of positive and negative words suggests that media attention can inflate asset prices in the presence of short-sale constraints as investors with the most optimistic valuations are able to buy while those with the most pessimistic valuations are unable to sell short./n"Outstanding Debt and the Household Portfolio," co-authored with my classmate Thomas A. Becker, alters a simple portfolio choice model to allow households to retire outstanding debt and realize a risk-free rate of return equal to the interest rate on that debt. Using the Survey of Consumer Finances we find that households with mortgage debt are 10 percent less likely to own stocks and 37 percent less likely to own bonds compared to similar households with no outstanding mortgage debt. To show that our results are not driven by irrational behavior amongst a subset of households, we construct two proxy variables for financial naivete. Finally we calculate the costs of non-optimal investment decisions in the presence of various forms of household debt including mortgages, home equity loans and credit card debt. We find that 26 percent of households should forego equity market participation on account of the high interest rates that they pay on their debt.

Advisor: Szeidl, Adam