VictorJuiz/thesis huggingface dataset:
Structural and biophysical studies of synaptic vesicle fusion machinery [electronic resource]
Keywords: Structural Biology.

A defining feature of eukaryotic cells is the compartmentalization of membrane-bound organelles with specialized functions. Movement of cargo between compartments, and exchange of material into and out of a cell are fundamental to cellular viability and effective communication with other cells. Secretion of neurotransmitters, the process by which neurons relay information, occurs when neurotransmitter-containing vesicles fuse with the target membrane in a pre-synaptic nerve terminal. Members of the SNARE, SM, and AAA+ ATPase protein families are central mediators of the exquisitely regulated process of neurotransmission. SNARE proteins form a complex that drives the fusion of synaptic vesicles with the target membrane; the SM protein Munc18a is a crucial mediator of SNARE complex assembly, and the ATPase NSF disassembles SNARE complex following neurotransmitter secretion, recycling SNAREs for subsequent rounds of vesicle fusion. The work presented here describes structural, biophysical, and biochemical approaches used to investigate the mechanism by which Munc18a, SNAREs and NSF orchestrate synaptic vesicle fusion.
Structuration, knowledge coordination, and profit [electronic resource] : modeling a microsociological theory of disequilibrium market dynamics
Keywords: Sociology.

To develop a microsociological theory of market dynamics, this dissertation formalizes a theory of the co-evolution of social structure, interaction, individual knowledge, system-level coordination, and system-level behavior. The dissertation parameterizes the formal theory using transaction-level data from and structural characteristics of the global steel market. Through a computational implementation of the parameterized theory, the dissertation explores microsociological origins of system-level dynamics. In markets with imperfect information, mechanisms of social structural reproduction govern a telephone game in which sequences of actions communicate path dependent and noisy signals about the universe of actors' preferences and constraints. Variance in the mechanisms of structural reproduction yield differently coordinated systems. Using archetypal comparisons, the dissertation reveals that this socially contextualized coordination influences system-level outcomes. The dissertation approaches markets as inherently social objects, but consciously mimics most aspects of economics' perfect competition, thereby illuminating markets' irreducibly social nature. The dissertation's computational implementation of formal theory extends economic sociology as a microsociological theory of market dynamics, and creates a bridge to economics by offering a sociological model of dynamic imperfect information.
Structure and dynamic processes in complex networks [electronic resource]
Keywords: Applied Physics.

The emergence of cyberspace gave rise to detailed traces of human behavior on-line, which results in an unprecedented opportunity to better understand the dynamics of social activities. Despite its diverse nature, the on-line behavior displays a number of strong regularities which can be understood by drawing on methods from statistical physics. This thesis first discusses statistical properties of a special kind of information network formed on-line, conversation threads, and more importantly, develops a dy- namical model which explains discrepancies in existing studies. It is also demon- strated that there are predictabilities of human interaction patterns by estimating mutual information of activity sequences. Additionally, properties of human behav- ior as a group, such as group purchasing and gathering, are scrutinized and modeled. And finally, diversity patterns of competing opinions/viruses diffused on network are modeled by investigating the formation of Turing pattern on large scale free networks.
Structure and dynamics of diffusion networks [electronic resource]
Keywords: Electrical Engineering.

Diffusion of information, ideas, behaviors and diseases are ubiquitous in nature and modern society. One of the main goals of this dissertation is to shed light on the hidden underlying structure of diffusion. To this aim, we developed flexible probabilistic models and inference algorithms that make minimal assumptions about the physical, biological or cognitive mechanisms responsible for diffusion. We avoid modeling the mechanisms underlying individual activations, and instead develop a data-driven approach which uses only the visible temporal traces diffusion generates. We first developed two algorithms, NetInf and MultiTree, that infer the network structure or skeleton over which diffusion takes place. However, both algorithms assume networks to be static and diffusion to occur at equal rates across different edges. We then developed NetRate, an algorithm that allows for static and dynamic networks with different rates across different edges. NetRate infers not only the network structure but also the rate of every edge. Finally, we develop a general theoretical framework of diffusion based on survival theory. Our models and algorithms provide computational lenses for understanding the structure and temporal dynamics that govern diffusion and may help towards forecasting, influencing and retarding diffusion, broadly construed. As an application, we study information propagation in the online media space. We find that the information network of media sites and blogs tends to have a core-periphery structure with a small set of core media sites that diffuse information to the rest of the Web. These sites tend to have stable circles of influence with more general news media sites acting as connectors between them. Information pathways for general recurrent topics are more stable across time than for on-going news events. Clusters of news media sites and blogs often emerge and vanish in matter of days for on-going news events. Major social movements and events involving civil population, such as the Libyan's civil war or Syria's uprise, lead to an increased amount of information pathways among blogs as well as in the overall increase in the network centrality of blogs and social media sites. Additionally, we apply our probabilistic framework of diffusion to the influence maximization problem and develop the algorithm MaxInf. Experiments on synthetic and real diffusion networks show that our algorithm outperforms other state of the art algorithms by considering the temporal dynamics of diffusion.
Structure and function of phosphoglucose isomerase in Colias eurytheme [electronic resource]
Keywords: Biology.

Butterflies belonging to the genus Colias are widespread throughout North America and populations are found in a diversity of habitats from lowland valleys to alpine grasslands and tundra. The thermal ecology of these habitats results in selective pressure on the metabolic enzymes in Colias to maximize flight performance, a key component of fitness for butterflies. Strong balancing selection on the glycolytic enzyme phosphoglucose isomerase (PGI) has produced persistent polymorphisms in many species. The evolutionary impacts of this polymorphism have been well studied and both heterozygote advantage for PGI and homozygote tradeoff of Vmax/Km versus thermals stability are known to be driving the balancing selection. This first study reported in the first chapter investigated the relationship between the structural polymorphisms of the PGI enzyme and the functional consequences that determine fitness. I pursued this by first reporting the native structure of PGI from Colias eurytheme as determined by x-ray crystallography. I then assayed the kcat / Km and thermal stability of three different homodimers of C. eurytheme PGI to demonstrate the tradeoff between the two functional characteristics in homodimers. Following this I used molecular dynamics simulations to investigate properties of the three homodimers that may be contributing to the observed functional differences. Those properties were hydrogen bonding patterns of the polymorphic sites, overall backbone movement, and distance between the catalytic residues. All three properties varied with with thermal stability and kcat / Km. The second set of experiments concerned the fixed difference at codon 370 between C. meadii and C. eurytheme. This fixed difference corresponded to the invasion of lowland habitats and is known to confer thermal stability to PGI. The evolutionary path of codon 370 from the ancestral glycine found in C. meadii and the derived serine found in C. euytheme would have required two mutations that would have produce either alanine or tryptophan as intermediate states. I expressed and assayed four homodimers that differ only at codon 370 and show that the mutation from glycine to serine exchanges kcat / Km for thermal stability as predicted. The putative intermediate alanine is similar to glycine, and the putative intermediate tryptophan has both poor kinetics and poor thermal stability. The results demonstrate that a single site change can make a large difference in modulating the tradeoff in homozygotes between kcat / Km and thermal stability and that the most likely evolutionary path was Gly → Ala → Ser at codon 370. Finally general results of the molecular dynamics approach are presented that reveal the stochastic nature of hydrogen bonding around polymorphic sites. A general trend between backbone carbon movement and charge-variant of the PGI dimer is also found.
Structure, dynamics and computation [electronic resource] : diverse applications of theory in neuroscience
Keywords: Physics.

How do the structure and dynamics of neural circuits conspire with circuit inputs to solve specific computational problems in the brain? In this thesis we use theory, often in coordination with experiment, to study several problems with relevance to this question. First, we use estimation theory to develop a measure of spatial resolution for stochastic localization microscopy that jointly depends on the density of fluorescent emitters, the precision of emitter localization, and prior information regarding the labeled object. This resolution measure clarifies the conditions under which optical methods suffice to measure neural circuit structure. Second, we use signal detection and estimation theory to quantify the physical limits set by photon shot noise for the optical detection and timing of neural spikes. This framework provides a quantitative benchmark for optical methods that measure the dynamics of neural circuits. Third, we combine time-lapse two-photon microendoscopy and mathematical modeling to track and quantify the dynamics of dendritic spines in the CA1 hippocampal area of living mice. Our results suggest new relationships between structure, dynamics, and function in the hippocampal circuit. Fourth, we treat visual motion estimation as a problem of Bayesian inference to determine how the optimal algorithm for motion estimation depends on the statistics of visual inputs. Our theory reveals that dark-light contrast asymmetries facilitate motion estimation with triple correlations. Finally, we show that fly and human visual systems jointly encode the direction and contrast polarity of moving edges using triple correlations that enhance motion estimation of natural stimuli. This striking convergence argues that the statistics of natural inputs have driven a common computational strategy for motion estimation across 500 million years of evolution. Collectively, these projects demonstrate several distinct and complementary ways that the integration of theory and experiment can accelerate progress in neuroscience.
Studies of bud-site selection in saccharomyces cerevisiae [electronic resource]
Keywords: Genetics.

This dissertation describes investigations of the machinery of cell polarization in the budding yeast Saccharomyces cerevisiae. Cell polarization is an essential feature of most, if not all, cell types. It occurs in two steps: (1) the selection of an axis and (2) the asymmetric organization of organelles, the cytoskeleton, and plasma-membrane components along this axis. The selection of an axis in S. cerevisiae is manifested as bud-site selection. S. cerevisiae cells select bud sites in either of two patterns, known as the axial and bipolar, depending on the mating type of the cells. Normal haploid cells use the axial pattern, whereas normal diploid cells use the bipolar pattern. Beginning with a re-analysis of the phenotypes of 38 mutants reported in a genome-wide screen to be defective in bipolar-bud-site selection, I focused on two groups of mutants with distinct phenotypes and tried to elucidate the molecular mechanisms underlying these phenotypes. The first group contains two mutants, bud13[Delta] and ist3[Delta]; the second group contains 14 endocytosis-related mutants. Each group has led to a separate story of how the corresponding proteins are involved in bipolar-bud-site selection. First, I found (Chapter 2) that Bud13 and Ist3 are responsible specifically for the efficient pre-mRNA splicing of MATa1, which encodes a cell-type-specific regulator for the expression of haploid-specific genes. One of these genes, AXL1, encodes a protein whose ectopic expression in diploid cells causes override of the bipolar-budding mechanism by the axial budding mechanism. Second, I found (Chapter 3) that endocytosis-related proteins are involved in maintaining the localization, and thus the function, of bipolar marker proteins including Bud8 and Bud9.
Studies of electrostatics and hydrogen bonds in human aldose and aldehyde reductase using a nitrile-containing inhibitor [electronic resource]
Keywords: Chemistry.

Human aldose reductase (hALR2) and human aldehyde reductase (hALR1) are both aldo-keto reductases with highly conserved tertiary structures. hALR2 is involved in the development of long-term, secondary diabetes complications. In light of the biomedical interest in developing selective hALR2 inhibitors against hALR1, nitrile vibrational probes were introduced into hALR2 and hALR1 through the binding of nitrile-containing inhibitors. These probes can provide information on microenvironments (e.g. electrostatics, hydrogen bonds) in the specificity pockets of similar proteins and help us understand inhibitor selectivity mechanisms. A new nitrile-containing inhibitor was designed and synthesized. The x-ray structure of its complex with wild type (WT) hALR2, along with cofactor NADP+, was determined. The nitrile is found to be in close proximity to T113, consistent with a hydrogen bond interaction. Two vibrational absorption peaks were observed at room temperature in the nitrile region when the inhibitor binds to WT hALR2, which were empirically assigned to hydrogen bonded and non-hydrogen bonded populations. IR studies on hALR2 mutants, classical molecular dynamics (MD) simulations, temperature dependent IR measurements, and 13C NMR-IR correlation experiments provide consistent, supportive evidence for this assignment from different perspectives. Hydrogen bonding interactions usually help to improve inhibitor potency; meanwhile, it also complicates the simplest analysis of vibrational frequency shifts as being due solely to electrostatic interactions through the vibrational Stark effect (VSE). VSE spectroscopy is an experimental technique which allows direct measurements of protein electrostatic fields. In order to examine the role of electrostatics as a possible selectivity determinant, VSE spectroscopy was used to measure electric fields in the active sites of hALR2 and hALR1 with nitrile vibrational probes. X-ray structures of two mutants, hALR2:T113A and hALR1:Y115A, in complex with the inhibitor and NADP+, were solved. Mutations to amino acid residues near the nitrile probe were made to convert the specificity pocket of one protein to the other, and vibrational frequency shifts were used to quantify the electrostatic differences in these two structurally similar proteins. MD simulations were performed to calculate protein electric fields, which were compared with measured fields. The applications of VSE spectroscopy in the investigation of important biological processes such as inhibitor selectivity are discussed.
A study of mid-latitude E-region anomalies in the ionosphere due to lightning [electronic resource]
Keywords: Aeronautics and Astronautics.

The goal of this research is to study the effects of lightning on the enhancement of ionization in the ionosphere. The ionosphere is a region of charged particles in the upper atmosphere and plays a significant role in high frequency radio communication. Any anomalous behaviour in the ionization properties of the ionosphere can potentially have adverse effects on radio users. While the upper regions of the ionosphere (200~km altitude and above) are well modeled and there exist instruments to provide a temporally and spatially good map of these regions, the lower ionosphere (60 to 200~km) is not as well understood due to limitations in continuous measurements of this region. Consequently, anomalous features in the lower ionospheric properties are not easily forecastable. It is hypothesized that certain features in the lower ionosphere are formed due to lightning and thunderstorm activity in the lower atmosphere, through convective mechanisms propagating upwards from the thunderstorm clouds to the ionosphere altitudes. We use an ionospheric model and lightning data for a 15 day period period from July 1 to July 15, 2010 over the continental USA, and use computational means to understand if there are any correlations between lower ionosphere anomalies and lightning. For the given data period and spatial domain, we find that there appears to be no statistically significant correlation between the two and further analysis is recommended.
Subgrid-scale turbulence modeling for improved large-eddy simulation of the atmospheric boundary layer [electronic resource]
Keywords: Civil and Environmental Engineering.

Large-eddy simulation (LES), as the name suggests, resolves the large eddies in the flow while modeling the effects of smaller motions (turbulence) on those larger eddies. Powerful computers make LES increasingly practical for analyzing a variety of atmospheric behavior in more detail, creating a need for more realistic turbulence models. Advances in describing atmospheric turbulence can impact many disciplines, e.g., weather and climate prediction, wind energy production, ocean dynamics, and, indeed, even computational fluid dynamics itself. Although the turbulence model can significantly affect the accuracy of the LES, simple turbulence models, which are known to be less accurate, are widely used. As an alternative, the Generalized Linear Algebraic Subgrid-Scale (GLASS) model, that actively couples momentum and heat transport, was developed. This model is more complete than conventional LES turbulence models because it accounts for additional transport processes. GLASS includes production, dissipation, pressure redistribution, and buoyancy terms. With the inclusion of an actively coupled turbulent heat flux model, GLASS is applicable to a range of atmospheric stability conditions for the unsaturated atmosphere. LES at various resolutions in a neutrally stratified boundary layer flow indicated that the GLASS model is a more physically complete subgrid-scale turbulence model that provides near-wall anisotropies and yields proper velocity profiles in the logarithmic layer. LES of the moderately convective boundary layer demonstrated that GLASS predicted the evolution of resolved quantities at least as well as the LESs with simple models, while including additional physics. Additional simulations of the stable boundary layer and the transitioning boundary layer highlight that GLASS can be applied to various stability conditions without the need of tuning model coefficients.
Sufficient statistics for team decision problems [electronic resource]
Keywords: Electrical Engineering.

Decentralized control problems involve multiple controllers, each having access to different measurements but working together to optimize a common objective. Despite being extremely difficult to solve in general, a common thread behind the more tractable cases is the identification of sufficient statistics for each controller, i.e. reductions of the measurements for each controller that do not sacrifice optimal performance. These sufficient statistics serve to greatly reduce the controller search space, thus making the problem easier to solve. In this dissertation, we develop for the first time a general theory of sufficient statistics for team decision problems, a fundamental type of decentralized control problem. We give rigorous definitions for team decisions and team sufficient statistics, and show how team decisions based only on these sufficient statistics do not affect optimal performance. In a similar spirit to the Kalman filter, we also show how to gracefully update the team sufficient statistics as the state evolves and additional measurements are collected. Finally, we show how to compute team sufficient statistics for partially nested problems, a large class of team decision problems that tend to have easier solutions. These team sufficient statistics have intuitive and compelling interpretations. We also show general conditions when these team sufficient statistics can be updated without the state growing in size. To illustrate the results, we give examples for finite-state systems and systems whose variables are jointly Gaussian.
Supersymmetric phenomenology at the large hadron collider [electronic resource]
Keywords: Physics.

This work investigates signatures of supersymmetry through the phenomenological Minimal Supersymmetric Standard Model (pMSSM), considering the collider and astrophysical implications that minimal supersymmetry may have. We scan over the 19-dimensional parameter space of the pMSSM, considering both the neutralino and gravitino as candidates for the lightest supersymmetric particle. We explore the sensitivity of the Large Hadron Collider to large sets of pMSSM models, and additionally consider the impact that current and future dark matter direct detection, indirect detection, and neutrino telescope experiments would have in constraining the pMSSM.