VictorJuiz/thesis huggingface dataset:
Selective inhibitors of the plasmodium proteasome as novel anti-malaria agents [electronic resource]

Malaria, a disease that affects millions of people in the world, is caused by the parasitic protozoan Plasmodium spp. In particular, Plasmodium falciparum leads to the most severe form of malaria and is especially lethal to young children. Although current anti-malaria medications are effective chemotherapeutics, the parasite can rapidly develop resistance to these agents and cases of resistance to even the first line of anti-malaria treatments have been reported. This increases the urgency to identify new malaria drugs and drug targets. In this thesis, I will first describe our efforts at identifying epoxyketone proteasome inhibitors that can attenuate Plasmodium growth with overall low host toxicity. We then synthesized activity based probes to monitor Plasmodium proteasome activity and together with subunit selective proteasome inhibitors, we assessed the importance of individual catalytic sites of the proteasome for parasite survival. We then screened covalent and non-covalent inhibitors against the catalytic site most crucial for parasite viability. Finally, we profiled the substrate cleavage signature of the P. falciparum proteasome and compared it to the human proteasome. We designed peptidic inhibitors based on dominant amino acid residues in the cleavages unique to P. falciparum proteasome. The inhibitor studies, along with cryo-electronmicroscopy structural elucidation of inhibitor bound Plasmodium proteasome, led us to the finding that the host and parasite [beta] 2 proteasome subunit have major differences in their substrate binding site. We then demonstrated how this difference could be exploited for design of potent and parasite selective proteasome inhibitor that was safely dosed in vivo. Taken together, this suggests that the Plasmodium proteasome is sufficiently different from the human proteasome for selective inhibition and promises to be an effective target for anti-malarial therapy.

Keywords: Chemical and Systems Biology.
Advisor: Bogyo Matthew
Boothroyd John C. advisor. Thesis advisor
Chen James
Mochly-Rosen Daria advisor. Thesis advisor
Self-pressurizing propellant tank dynamics [electronic resource]

Hybrid rockets frequently use nitrous oxide as a self-pressurizing oxidizer, where the high vapor pressure of the oxidizer is used to force the liquid out of the propellant tank and into the combustion chamber. To study this system, a series of small-scale pressure vessels with optical access have been developed that can be filled with nitrous oxide and then drained in a manner that replicates the conditions within a hybrid rocket. A high-speed camera has been used to visualize the nitrous oxide within the propellant tank and identify relevant phenomena. Experiments have identified two separate temporal regimes that are common to all blowdown tests: a transient and steady state, each described by distinct features. The transient regime is characterized by a rapid pressure drop and recovery, with homogeneous condensation of the ullage and heterogeneous nucleation and growth of bubbles. During steady state regime the liquid and vapor are both homogeneous two-phase mixtures and the pressure drops in a linear fashion as the liquid drains from the tank. Carbon dioxide was identified as a possible simulant fluid for nitrous oxide, and comparison tests showed that it behaves as an accurate analog. This low-cost and safe simulant fluid enabled a large number of tests that examined the effect of parameter variations, including flow rate, fill level, temperature, and scaling effects. Experimental data from this system have been used to develop a new model for self-pressurizing propellant tank dynamics. This was done by blending the 0-D lumped-node methods of previous researchers with a novel 1-D method that captures the dynamics of a changing bubble population. The direct quadrature method of moments was used to develop partial differential equations for parameters of this distribution. The proposed model was compared against experimental data and shown to have good agreement. The pressure drop and recovery seen in the transient regime, which is not captured by previous models, is visible in the model predictions. Convergence studies were performed in order to determine suitable parameters of the numerical integration schemes and the discretizations used. To complete the model, numerous submodels were incorporated by using relations from various sources in the literature. The effect of variations in these submodels was studied in order to justify the selection of adjustable constants.

Keywords: Aeronautics and Astronautics.
Advisor: Cantwell Brian primary advisor. Thesis advisor
Alonso Juan José
Zilliac Gregory G.
Sensory substitution and augmentation of forces and torques using tactile skin deformation feedback [electronic resource]

Haptic devices aim to render a realistic sense of touch using kinesthetic and tactile feedback. Kinesthetic feedback provides forces and torques that affect the motion of the user's hand or arm. Tactile feedback stimulates cutaneous receptors in the user's skin. Currently, most commercial haptic devices aim to provide kinesthetic feedback. Although kinesthetic feedback can convey multiple degree-of-freedom information intuitively to the user, this type of feedback can potentially be destabilizing. In contrast, tactile feedback can be used to create the perception of forces and torques without physically imparting these forces and torques to the user, and is not destabilizing. However, conveying multi-degree-of-freedom force and torque information via the tactile channel, in a manner that is intuitive to a human user, can be challenging. This thesis focuses on the design, development, and experimental validation of a class of tactile feedback devices that provide feedback using local fingerpad skin deformation. Fingerpad skin deformation occurs in our daily interaction with objects, feels natural, and can intuitively express many degrees-of-freedom. Skin deformation tactile feedback can provide force and torque information through skin deformation cues on multiple fingers in a manner that is consistent with our interaction with external objects. This thesis describes several novel skin deformation feedback devices and shows in human participant studies that skin deformation feedback influences perception of stiffness. Skin deformation feedback can be used in conjunction with force feedback to improve the perception of stiffness of virtual surfaces, and can also be employed for sensory substitution and augmentation of force and/or torque information during manipulation of objects in virtual environment or teleoperation scenarios. When skin deformation feedback was used as a form of sensory substitution to convey force/torque information, study participants improved task performance compared to when no feedback was given. When skin deformation feedback was used to augment kinesthetic feedback to provide additional force/torque information, subject participants showed improvements in task performance compared to only kinesthetic feedback. The results of this thesis show that skin deformation tactile feedback is intuitive, and can be used to convey force and torque information to substitute, or augment, kinesthetic feedback. Skin deformation tactile feedback is potentially useful in scenarios where the provision of kinesthetic force and/or torque feedback is difficult, notably in teleoperated robot-assisted surgery, space and underwater teleoperation, where kinesthetic feedback may cause system instability.

Keywords: Mechanical Engineering.
Advisor: Cutkosky Mark R. primary advisor. Thesis advisor
Okamura Allison primary advisor. Thesis advisor
Khatib Oussama advisor. Thesis advisor
Provancher William
The separation and imaging of continuously recorded seismic data [electronic resource]

Imaging targets for exploration seismology surveys are increasingly associated with subsurface conditions that pose serious challenges for both seismic model building and imaging. In particular, these zones of interest are often sub-salt, and can feature dipping, anisotropic overburdens. In order to construct representative Earth models, and hence an accurate image, reflection datasets with large offsets, high levels of reflection point redundancy, and rich azimuthal coverage are sought. This creates a requirement for denser and more efficient field acquisition techniques, which can be achieved through blended data acquisition. Here, multiple source points are acquired simultaneously and receivers continuously record the overlapping wavefields. Separating these simultaneously acquired seismic data into their conventionally acquired equivalent is the link between more efficient data acquisition and conventional imaging and model building techniques. The focus of this thesis is the development of a robust methodology for taking these continuously recorded, blended datasets and accurately separating each shot into an individual record, free from blending contamination. Successful existing techniques unanimously feature strict requirements on the randomness of the source distribution during acquisition, as a consequence, a technique which can separate data with repeatable delay patterns is demonstrated. By using extended seismic migration and inverse forward modeling, separation is demonstrated which is less sensitive to shooting pattern. The image space has several features amenable to the separation problem; it is of lower dimensionality, it has a higher signal-to-noise ratio and methods such as preconditioning and regularization can be employed. Images with a reduced quantity of interference-related noise are created, then a forward modeling process provides a separated output dataset. While forward modeling alone provides a high level of separation, amplitudes subleties of these input data can be lost. By posing the data recovery process as an inverse problem, representative amplitude character is recovered. Posing the problem in the extended image space relaxes requirements on the accuracy of the migration velocity model. This extended space preserves all kinematic and amplitude information present in the input data, and there is no loss of information during imaging. This methodology is demonstrated on three synthetic datasets, of varying complexity, and a 3D Ocean Bottom Node dataset. Qualitative and quantitative comparisons for the synthetic tests show the separation is accurate to the order of 5% after ten iterations. Qualitative analysis of the OBN separation shows that comparable images are achieved after separation, compared to an unblended input dataset.

Keywords: Geophysics.
Advisor: Biondi Biondo
Clapp Robert G. (Robert Graham)
Mavko Gary
A sequential Monte Carlo approach to joint longitudinal and time-to-event modeling [electronic resource]

The statistical modeling framework known as joint longitudinal/time-to-event modeling (joint modeling) has enabled researchers to combine the benefits of two important modeling paradigms in a unified fashion, as it aims to capture the interrelatedness of the respective models while delivering improvements in efficiency and inferential validity. Much of this work has evolved in the biostatistical setting, where researchers wish to account for the interrelationship between dynamically-evolving biological processes and survival time distributions. The vast majority of estimation techniques for joint modeling have been developed in the maximum-likelihood framework. While Bayesian analyses do exist, their practicality is hindered by the typical computational drawbacks associated with classical Markov Chain Monte Carlo estimation techniques, which do not generalize to longitudinal settings in which one may desire to perform online analyses. In this thesis, after a comprehensive review of joint modeling, we describe a new approach to Bayesian estimation of general state space models which provides a solution to the joint state and parameter estimation in an online fashion. As a means to this end, we describe the development of a computationally efficient alternative to traditional Bayesian inference by Markov Chain Monte Carlo (MCMC) methods, and explain how it can be incorporated into a novel adaptive sequential Monte Carlo framework to allow for fast and accurate estimation of model states and parameters. We then describe how a general joint longitudinal/time-to-event model may be constructed in a state space context, and carry out detailed simulation studies to illustrate the performance of the algorithm and utility of the model. We conclude that approaching joint longitudinal/time-to-event models through the prism of state space modeling offers a new and constructive perspective on an important modern statistical framework.

Advisor: Lai T. L. primary advisor. Thesis advisor
Lavori Philip W.
Shih Mei-Chiung advisor. Thesis advisor
Shape optimization in adaptive search spaces [electronic resource]

Design space dimensionality is a persistent obstacle to high-fidelity aerodynamic shape optimization. The burden typically falls to the designer to select the shape design variables, which restricts the design space and impacts computational efficiency. In this work, I develop a system that automatically adapts the shape parameterization to efficiently solve the given design problem. Optimization begins with a small set of design variables, which is then progressively refined to enable the discovery of superior designs. The adaptation is goal-oriented and is driven by a novel refinement indicator that focuses shape control resolution on regions with the highest potential to improve the design. This indicator is computed from adjoint sensitivity information and a quasi-Newton Hessian approximation, which are both readily available in many design frameworks. To verify that the system can autonomously discover parameters sufficient to solve a problem, three inverse design problems are examined. For these cases, the procedure robustly converges to the continuous optimum from different starting points and with different refinement strategies. Several airfoil and wing shape optimization problems are then performed. The adaptive approach generally yields smoother design trajectories, at substantially lower cost than under fixed or uniformly-refined parameterizations. Finally, I consider the combinatorial problem of finding an optimal layout for an adaptive, trailing edge flap system. In fewer than 100 simulations, the adaptive procedure discovers a flap layout that outperforms naive layouts. I conclude with a discussion of the tremendous potential this approach offers for many other disciplines and design environments.

Keywords: Aeronautics and Astronautics.
Advisor: Jameson Antony
Aftosmis Michael J.
Alonso Juan José
Shared vehicle control using safe driving envelopes for obstacle avoidance and stability [electronic resource]

Recent trends in automotive crash statistics suggest a dual role of technology in both saving and threatening the lives of American drivers. Advancements in automotive safety like Anti-Lock Braking Systems and Electronic Stability Control have led to a significant reduction in automotive fatalities over the last decade. However, the ubiquity of technology, mainly the cellular phone, has led to a dramatic increase in fatalities attributed to distracted driving. To address this challenge, auto manufacturers are empowering modern vehicles with even more technology. Advanced sensors provide real-time information about the surrounding environment. By-wire actuators, which allow drivers indirect command of the vehicle through an electronic pathway, enable vehicle safety systems to share control with a driver through augmentation of the driver's commands. This technology combination gives safety systems an unprecedented amount of authority to react to the vehicle's newly perceived world. Leveraging these advancements in vehicle actuation and sensing, this dissertation presents a shared control framework for obstacle avoidance and stability control using safe driving envelopes. One of these envelopes is defined by the vehicle handling limits while the other is defined by spatial limitations imposed by lane boundaries and obstacles. A Model Predictive Control (MPC) scheme determines at each time step if the current driver command allows for a safe vehicle trajectory within these two envelopes, intervening only when such a trajectory does not exist. A sparsity seeking objective in the MPC formulation serves as a simple and effective approach to shared control between a human driver and an automated machine. In this way, the controller seeks to identically match the driver's commands whenever possible while avoiding obstacles and preventing loss of control. Computationally efficient models of the environment, the vehicle, and the handling limits allow for real-time prediction of dangerous scenarios over a 4 (s) horizon. This advanced warning enables the use of brake actuation to ensure safe vehicle trajectories that adhere to both safe envelopes, providing an envelope of protection through augmentation of a driver's steering, braking, and throttle commands. The optimal control problem underlying the controller is inherently non-convex but is solved as a set of convex problems allowing for reliable, real-time implementation that is executed at 100 (Hz). This approach is validated on an experimental vehicle working with human drivers to negotiate obstacles in low friction environments.

Keywords: Mechanical Engineering.
Advisor: Gerdes J. Christian primary advisor. Thesis advisor
Boyd Stephen P. advisor. Thesis advisor
Pavone Marco
Sharing costs to optimize network equilibria [electronic resource]

Congestion games are a fundamental class of applications in the study of strategic behavior in large systems. In congestion games, selfish individuals act as consumers of resources at local parts of the system. These individuals typically obey their own self-interests and will not necessarily adhere to the prescriptions of a socially optimal solution. Imposing centralized control upon these individuals is infeasible, but the deployment of simple rules at a local level can limit the discrepancy between the individual goals of the system users and the global optimization objectives of the system designer. Such rules can be abstracted as cost sharing methods that distribute the joint cost on a resource among those who generate it. This thesis aims to present a comprehensive study of cost sharing as a means of decentralized control in congestion games and their generalizations.

Keywords: Management Science and Engineering.
Advisor: Roughgarden Tim primary advisor. Thesis advisor
Goel Ashish advisor. Thesis advisor
Ye Yinyu advisor. Thesis advisor
Simulation of hypersonic flow within electromagnetic fields [electronic resource]

Space vehicles that enter the atmosphere require the use of a Thermal Protection System (TPS) to protect them from aerodynamic heating. The TPS currently in use is composed of a heat-resistant material to protect the inner part of the vehicle, and it adds tremendously to the cost of a space mission. In contrast, it has been pointed out that such a high enthalpy gas flow, which is partially ionized, could be controlled through an electromagnetic effect, and as a result, the high convective heat could be reduced, and furthermore, the aerodynamic force acting on the vehicle could be controlled. A lot of research has been carried out, not only theoretically but also experimentally, to understand the electromagnetic effect. However, numerical accuracy in predicting these effects, especially for heat flux mitigation, has not been satisfactory. Accurate simulation of such flows requires the solution of the Navier-Stokes equations for compressible viscous flow, and for the equations describing the state of the high temperature gas containing many species in chemical and thermal equilibrium or non-equilibrium. In addition, Maxwell's equations for including the effects of electromagnetic fields upon an ionized hypersonic flow through Lorentz forces and Joule heating need to be solved in order to realize flow control advantages. Inclusion of these three sets of equations in the numerical simulation of hypersonic flow is computationally intensive and stiff to solve. Therefore, many researchers have made a number of simplifications based on certain assumptions to reduce the size of the governing equations. However, these simplifications and assumptions are not valid under certain flight regimes and can lead to inaccurate estimates of heat flux to the vehicle. In this thesis, the full magneto fluid dynamics (MFD) equations, including multi-species, chemical reactions, and Maxwell's equations, have been solved. The approach includes formulation of the full governing equations, the boundary conditions including catalytic, cold wall boundaries, and the numerical procedure for solving the governing equations. The solver is verified and validated with experimental data provided by Ziemer for shock stand-off distance, by Gulhan et al. and Kawamura et al. for heat flux mitigation. The numerical results show an excellent match with previously published experimental data.

Keywords: Aeronautics and Astronautics.
Advisor: Cantwell Brian primary advisor. Thesis advisor
MacCormack R. W. (Robert William)
Alonso Juan José
Simultaneous dual-beam optical trap and sm-fret probing long-range tertiary interactions in tpp riboswitch [electronic resource]

RNAs are ubiquitous in virtually all biological processes and its function is based on their 3D structures. From sequence to 3D structure, its ability to carry genetic information and function like proteins shows remnants of a RNA world (Breaker, 2012). Riboswitches are evidence of a RNA world as they are cis-regulatory elements formed in mRNA that can modify gene expression in response to environmental cues. A well-known example is the thiamine pyrophosphate (TPP) riboswitch, whose specificity for TPP is dependent upon conformational changes that take place within its ligand-binding aptamer region. Here, the role of tertiary interactions in ligand binding is studied at the single-molecule level by combined force spectroscopy and Fӧrster resonance energy transfer (smFRET), using a dual-beam optical trapping apparatus equipped for simultaneous, spatially coincident smFRET. Detailed calibrations and optimization of the "Force-FRET" technique are performed using several well-characterized DNA hairpins by force spectroscopy. Extending this approach, we directly probe secondary and tertiary structural changes during TPP aptamer folding, including key events associated with ligand binding. The concurrent transitions observed in smFRET signals and RNA length changes revealed differences in helix arm orientation between two previously-identified ligand-binding states that were undetectable by force spectroscopy alone. With our Force-FRET technique, we can resolve the structural details of the weaker binding state when fully bind to TPP, and identify the mechanism behind its inability to form the tertiary interaction that completes the TPP binding process. This powerful single-molecule technique enhances our understanding of how tertiary interactions play a crucial role in stabilizing global riboswitch structure and, ultimately, in increasing ligand specificity. Further investigation of these multidimensional energy landscape for RNA folding require development of techniques, such as Force-FRET, that can probe this landscape with more than one reaction coordinate. This development enables us to ask more complicated questions such as coupling transcription-translation and observing both processivity and conformational changes of these proteins.

Keywords: Biophysics.
Advisor: Block Steven M.
Das Rhiju
Dunn Alexander Robert advisor. Thesis advisor
Riedel-Kruse Hans