VictorJuiz/thesis huggingface dataset:
Drag augmentation via supersonic retropropulsion for atmospheric deceleration [electronic resource]

With sample-return and manned missions on the horizon for Mars exploration, the ability to decelerate high-mass systems upon arrival at a planet's surface has become a research priority. Mars' thin atmosphere necessitates the use of advanced entry, descent, and landing (EDL) systems to aid in deceleration to sufficiently low terminal descent velocities, and the limits of current state-of-the-art Mars EDL technologies are being challenged by evolving mission requirements. Supersonic retropropulsion (SRP), the application of jets facing into the freestream during the supersonic portion of flight, has been proposed as a candidate enabling technology for future high-mass Mars missions. Moving beyond the current "jets as thrust" paradigm, this work explores augmentation of the decelerative forces experienced during Mars entry through a flow control approach which increases aerodynamic drag through SRP jet manipulation of the bow shock. A drag augmentation model is developed based upon attainable shock physics seen in high-fidelity simulations of SRP jets. This flow model uses SRP jet manipulation to recover shock losses normally associated with the strong high-Mach number bow shock on the entry vehicle. Flow control through SRP allows for partial recovery of stagnation pressure and thus significant deceleration without the burden of substantial fuel mass, increasing both the mass of deliverable payloads and the payload mass fraction. To quantify maximum achievable benefits, an analytical study determines the upper limit on drag coefficients for probable jet-induced cascading shock structures (oblique shocks followed by a normal shock). Subsequent trajectory studies reveal a tremendous potential for aerodynamic drag generation which is substantial even if only a modicum of the stagnation pressure losses can be recovered through SRP shock manipulation. Finally, attainable drag coefficient values and candidate configurations are presented based on well-validated CFD simulations of modeled jets and the resulting shock structures, establishing this novel SRP-based flow control concept as a technology capable of increasing the deliverable payload mass for future Mars missions.

Keywords: Aeronautics and Astronautics
Advisor: Alonso Juan José
Cantwell Brian advisor. Thesis advisor
MacCormack R. W. (Robert William)
Aftosmis Michael J. advisor. Thesis advisor
The Drosophila Myb and RB/E2F2 complex transcriptionally regulates cytokinesis [electronic resource]

The Myb gene family plays a role in several types of human cancers. For example, high expression levels of c-Myb in colon cancer and B-Myb in breast cancer correlated with poor prognosis for the patient. B-Myb, the vertebrate homolog of invertebrate Myb, activates transcription of mitotic genes. In Drosophila, mutation of Myb reduced expression of mitotic genes, such as the regulatory kinase genes polo and ial (AurB). Previous studies revealed multiple mitotic defects in Myb mutant cells, including disrupted chromosome condensation and abnormal spindles. I now show that binucleate cells, the hallmark phenotype of cytokinesis failure, accumulate in Myb-null ovarian follicle cell and wing disc epithelia. Myb functions as an activator in the generally repressive Drosophila RBF, E2F2, and Myb (dREAM)/Myb-MuvB complex. Absence of the dREAM subunits Mip130 or E2F2 suppressed the Myb-null cytokinesis defect. While previous Myb-null mitotic phenotypes were difficult to quantitatively assay, the binucleate phenotype was binary, countable, and had a near zero background level in wild-type tissues. This offered a unique opportunity to use the Myb-null binucleate phenotype to study how the dREAM complex represses transcription. In the absence of Myb, repression by the dREAM complex was sensitive to the decreased dose of the subunits E2F2, Mip120, Caf1, and interestingly Lin-52, which was previously genetically implicated as an activator in the complex. Surprisingly, reducing the dose of His2Av also suppressed the Myb-null binucleate phenotype, suggesting a novel role for this variant histone in transcriptional repression by the dREAM complex.

Keywords: Genetics
Advisor: Lipsick Joseph Steven
Fuller Margaret
Sage Julien advisor. Thesis advisor
Stearns Tim advisor. Thesis advisor
Dual-band CMOS power amplifiers [electronic resource]

The past five years have seen the explosive growth of smartphones and tablets. In 2011, worldwide smartphone sales reached 473 million units, and since the iPad's launch in 2010, it has sold 84.1 million units. These popular mobile devices connect to a variety of wireless standards, such as Wi-Fi, Bluetooth, FM radio, GPS, and cellular, which each operate in different frequency bands. Today each frequency band requires its own wireless radio, but there is an effort to design dual-band radios capable of operating across multiple frequencies. These dual-band radios could reduce components, lower costs, and improve the energy efficiency in wireless devices. Some RF circuit blocks, such as the voltage-controlled oscillator (VCO) and low-noise amplifier (LNA), have already been designed in dual-band, but a dual-band power amplifier (PA) has remained elusive. This thesis investigates dual-band PAs in CMOS for the 802.11n WLAN standard that operates in both 2.4GHz and 5.0GHz bands. First a broadband PA that could cover both frequencies, 2.0GHz to 5.0GHz, was designed. The disadvantage of this approach was the strong 2.4GHz second harmonic at 4.8GHz that fell within the broadband range. Normally a filter could be placed after the PA to eliminate this second harmonic, but with a dual-band 2.4GHz / 5.0GHz PA, a filter cannot eliminate the 4.8GHz second harmonic without also severely degrading the 5.0GHz signal. So then tunable filters, both on-chip and off-chip, were designed to eliminate the second harmonic only during 2.4GHz operation. First a PA with on-chip tunable filter that could also serve as a dual-band matching network was designed. Next an off-chip tunable filter on PCB using discrete components was designed. This off-chip tunable filter was then integrated with the broadband and dual-band PAs to show second harmonic filtering using both on-chip and off-chip filters.

Keywords: Electrical Engineering
Advisor: Lee Thomas primary advisor. Thesis advisor
Wong S. Simon primary advisor. Thesis advisor
Dutton Robert R. advisor. Thesis advisor
Dynamic amplifiers for high-speed pipelined A/D conversion [electronic resource]

Analog-to-digital converters (ADC) are a vital part of a many applications that require an interface with real-world analog signals. Fueled by the ever increasing demand for higher bandwidth and lower power consumption in many areas, the energy efficiency of ADCs becomes a critical performance criterion. Today, there exist a variety of ADCs that provide high energy efficiency solutions only for low bandwidths (below ~100 MHz). In the high-speed space (above 100 MHz), however, the energy efficiency of ADCs degrades dramatically, and this is especially visible for pipelined ADCs, which take 3-5 times more energy than other architectures that do not emphasize high speed. Furthermore, existing non-pipelined solutions for this bandwidth range are few in numbers, and this presents an opportunity for innovation at both the architectural and circuit design level. This thesis explores a pipelined ADC design that employs a variety of low-power techniques such as dynamic residue amplification and incomplete settling in a unique way to maximize the speed while maintaining low energy (98 fJ/conv-step). The resulting work advances the state-of-the-art by simultaneously achieving a high conversion rate (500 MS/s), low power (5.1 mW), moderate resolution (8 bits), and low input capacitance (55 fF). The experimental converter was implemented in a 65-nm Silicon-on-Insulator (SOI) CMOS process and is among the first high-performance ADCs employing this technology.

Keywords: Electrical Engineering
Advisor: Murmann Boris primary advisor. Thesis advisor
Horowitz Mark (Mark Alan) advisor. Thesis advisor
Wooley Bruce A.
Dynamic analysis of markets [electronic resource]

We study learning in a dynamic setting where identical copies of a good are sold over time through a sequence of second price auctions. Each agent in the market has an unknown independent private valuation which determines the distribution of the reward she obtains from the good; for example, in sponsored search settings, advertisers may initially be unsure of the value of a click. Though the induced dynamic game is complex, we simplify analysis of the market using an approximation methodology known as mean field equilibrium (MFE). The methodology assumes that agents optimize only with respect to long run average estimates of the distribution of other players' bids. We show a remarkable fact: in a mean field equilibrium, the agent has an optimal strategy where she bids truthfully according to a conjoint valuation. The conjoint valuation is the sum of her current expected valuation, together with an overbid amount that is exactly the expected marginal benefit to one additional observation about her true private valuation. Under mild conditions on the model, we show that an MFE exists, and that it is a good approximation to a rational agent's behavior as the number of agents increases. Formally, if every agent except one follows the MFE strategy, then the remaining agent's loss on playing the MFE strategy converges to zero as the number of agents in the market increases. We conclude by discussing the implications of the auction format and design on the auctioneer's revenue. In particular, we establish a dynamic version of the revenue equivalence theorem, and discuss optimal selection of reserve prices in dynamic auctions.

Keywords: Management Science and Engineering
Advisor: Johari Ramesh
Glynn Peter W. advisor. Thesis advisor
Van Roy Benjamin advisor. Thesis advisor
Dynamic learning mechanisms in revenue management problems [electronic resource]

One of the major challenges in revenue management problems is the uncertainty of the customer's demand. In many practical problems, the decision maker can only observe realized demand over time, but not the underlying demand. Methods to incorporate demand learning into revenue management problems remain an important topic both for academic researchers and practitioners. In this dissertation, we propose a class of dynamic learning mechanisms for a broad range of revenue management problems. Unlike methods that attempt to deduce customer demand before the selling season, our proposed mechanisms enable a decision maker to learn the demand "on the fly''. That is, they integrate learning and doing into a concurrent procedure and both learning and doing are accomplished during the selling season. Furthermore, we show that our mechanisms are 1) Robust, that is, our mechanisms work well for a wide range of underlying demand structures and do not need to know the structure beforehand; 2) Dynamic, that is, our mechanisms take advantages of increasing sales data as selling season moves forward and update the demand information along the process and 3) Optimal, that is, our mechanisms achieve near-optimal revenues, as compared to a clairvoyant who has complete knowledge of the demand information beforehand. By comparing with different learning mechanisms, we claim that "dynamic learning" is essential for our mechanism to achieve improved performance and the above features. We consider two widely-used models in this dissertation, a customer bidding model and a posted-price model. For each model, we describe a dynamic learning mechanism with theoretical guarantee of near-optimal performance. Although different models entail different mechanism details and different analysis tools, we show that a common denominator is that the improvement of our mechanisms comes from one unique feature: dynamic learning. We also present numerical tests for both models from which the performance of our mechanisms is verified. We believe that the dynamic learning mechanisms presented in this dissertation have important implications for both researchers and practitioners.

Keywords: Management Science and Engineering
Advisor: Ye Yinyu primary advisor. Thesis advisor
Glynn Peter W. advisor. Thesis advisor
Lai T. L. advisor. Thesis advisor
Dynamic offset cancellation for MEMS accelerometers [electronic resource]

Today's Micro-Electromechanical Systems (MEMS) accelerometers suffer from input offsets that drift with temperature and time. These devices are calibrated once after fabrication in order to cancel their offset. In order to cancel the offset drift over temperature, the temperature is swept during the post-fabrication calibration and the offset is recorded as a function of temperature. However, the residual offset drifts over the life-time of the device, and cannot be cancelled by a one-time factory calibration. With the continuously increasing precision requirements of accelerometers, this offset drift is emerging as an issue. This dissertation presents a new approach that dynamically measures and cancels a major part of the offset drift that is due to change in parasitic capacitance of the bondwires in a system-in-package-type MEMS accelerometer. This approach is based on modulation of the spring constant of the sensor element by applying a modulating electrostatic force. A prototype interface IC was fabricated in a 0.18-[mu]m 3-V CMOS technology, and was packaged and tested with a MEMS sensor element. The CMOS readout dissipates 3.1 mW, and has a noise-floor of 220 [mu]g/√Hz. The bandwidth of the interface is 1 kHz with a usable bandwidth of 200 Hz. The full-scale range is 9.14 g. The proposed scheme reduces the bondwire offset of a prototype by a factor of 112 (41dB).

Keywords: Electrical Engineering
Advisor: Murmann Boris primary advisor. Thesis advisor
Howe Roger Thomas advisor. Thesis advisor
Wooley Bruce A.
Dynamic portfolio management with private equity funds [electronic resource]

Private equity investments have become an increasingly significant portion of many institutional portfolios because of their attractive return characteristics. However, despite being illiquid and having inherently multi-period cashflow characteristics, portfolio management techniques involving private equity asset classes are still dominated by traditional but largely inadequate single period approaches. In this work, I propose a quantitative modeling approach and a portfolio optimization framework to handle funds with significant private equity investments. Driven by the demands of practical application, the key features of this approach are that it captures the unique illiquid and multi-period characteristics of private equity while remaining computationally simple. In fact, the computation required is not significantly more difficult than that required for single period mean-variance portfolio optimization. I use a state space model to capture the aggregate dynamics of each private equity asset class. If desired, the number of states in this model can be increased to more accurately reflect the cashflow characteristics of the asset class. Using the model, a multi-period mean-variance portfolio optimization problem is formulated, and a suboptimal open-loop approach is employed for its computational simplicity. Based on this open-loop problem, I also propose a shrinking horizon implementation that is provably superior to the open-loop solution that it is based on. Numerical examples are used to compare the open-loop approach to other commonly used heuristic approaches. An example using statistics reflective of a large university endowment fund is solved and insight into portfolio management with private equity asset classes is highlighted. Finally, using the developed multi-period open loop approach, I develop a heuristic method that utilizes the single-period methods that most investors still rely on. The heuristic method is derived by adjusting the mean and variance of the returns of the private equity asset classes, and can be interpreted in the context of a liquidity premium.

Keywords: Electrical Engineering
Advisor: Boyd Stephen P. primary advisor. Thesis advisor
Primbs James primary advisor. Thesis advisor
Lai T. L. advisor. Thesis advisor
Dynamic pricing in the airline industry [electronic resource]

The dissertation consists of two essays on different aspects of dynamic pricing with applications to the U.S. airline industry. The first essay studies how a firm's ability to price discriminate over time affects production, product quality, and product allocation among consumers. The theoretical model has forward-looking heterogeneous consumers who face a monopoly firm. I use this model to study the time paths of prices for airline tickets offered on monopoly routes in the U.S. Using estimates of the model's demand and cost parameters, I compare the welfare travelers receive under the current system to several alternative systems, including one in which free resale of airline tickets is allowed. The second essay, motivated by pricing practices in the airline industry, studies the incentives of players to publicly and independently limit the sets of actions they play later in a game. I find that to benefit from self-restraint, players have to exclude all actions that create deviations for them and keep some actions that can deter deviations of others. I develop a set of conditions under which these strategies form a subgame perfect equilibrium and show that in a Bertrand oligopoly, firms can mutually gain from self-restraint, while in a Cournot oligopoly they cannot.

Keywords: Business.
Advisor: Benkard C. Lanier primary advisor. Thesis advisor
Reiss Peter C. (Peter Clemens) primary advisor. Thesis advisor
Skrzypacz Andrzej
Dynamics and mechanics of the actin cytoskeleton ex vivo [electronic resource]

In actin-based crawling motility, cells continuously build, reorganize, and disassemble an actin network in a process driven jointly by biochemical reactions and mechanical work. Herein, we use isolated actin cytoskeletons from fish epithelial keratocytes to study two aspects of this highly coordinated process. For the continuous actin network of a motile cell to drive translocation, net assembly of the actin network at the leading edge (which drives protrusion) must be balanced by net disassembly at the trailing edge. Although proteins such as ADF/cofilin and gelsolin are known to locally depolymerize actin filaments, it is not clear how such activity could be coordinated with assembly over the distance scale of the whole cell. Here we present experiments showing that activation of nonmuscle myosin II embedded in isolated cytoskeletons results in partial disassembly of the actin network. Taken together with prior work on the effect of myosin II inhibition in live cells, these results establish that myosin II contributes to actin network disassembly in the rear of motile cells, and suggest that gradual binding of myosin to a maturing actin network could serve as a mechanism to coordinate actin network assembly and disassembly over long distances. A thorough understanding of how forces produced by actin and myosin contribute to whole-cell movement will require detailed knowledge of the material properties of the cytoskeletal network at the relevant spatial and temporal scales. Measurements of mechanical properties have largely been limited to microscopic strains, whole-cell bulk measurements, or reconstituted gels that do not fully capture the cellular cytoskeletal organization. We have therefore sought to characterize the deformation of actin networks derived from motile cells under large applied strains. Strain could be applied to the lamellipodial actin network by displacing the cell body using a glass microneedle. The network behaves as a coherent material sheet that is mechanically well-coupled to the cell body and stretches to approximately 400% of its original dimensions. At smaller strains and time scales ranging from a fraction of a second to tens of seconds, the network behaves almost exclusively elastically, suggesting that the cytoskeletal network is capable of integrating and transmitting forces over large distances within the cell.

Keywords: Biochemistry
Advisor: Theriot Julie primary advisor. Thesis advisor
Dunn Alexander Robert advisor. Thesis advisor
Herschlag Daniel advisor. Thesis advisor
Spudich James A.
Economic analysis of HIV prevention and treatment portfolios [electronic resource]

Human immunodeficiency virus (HIV) is a significant problem worldwide as well as in the United States (US), despite ongoing efforts to limit HIV transmission. In the US, men who have sex with men (MSM) account for over half of new HIV infections every year, and thus are an important group to consider for HIV interventions. Both prevention and treatment options are available to combat HIV transmission, but decision makers must prioritize among the available disease control strategies. Mathematical modeling frameworks can be used to assess the value and efficiency of various disease control measures and help inform resource allocation decisions. This dissertation describes research on economic analysis of HIV prevention and treatment portfolios, primarily for MSM in the US. We develop two independent mathematical modeling frameworks, both intended to assist decision makers with minimizing HIV transmission in the most cost-effective manner. First, in Chapter 2, we present a dynamic compartmental model of the HIV epidemic that we built and instantiated for MSM in the US. This model can be used to assess the effectiveness and cost-effectiveness of prevention and treatment programs for MSM. In particular, in Chapter 3 we examine testing for and treating acute HIV infection, and in Chapter 4 we examine preexposure prophylaxis for HIV prevention. We find that symptom-based testing for acute HIV infection is cost-effective for MSM in the US, but incorporating testing for acute infection into the standard HIV screening protocol is not. For preexposure prophylaxis, we find that it is not cost-effective for the general MSM population, but it provides good value in high-risk MSM. In Chapter 5, we present a resource allocation framework for determining the optimal mix of HIV treatment and prevention programs, given a fixed budget. We develop methods of linearly estimating health benefits and costs that account for epidemic effects of reducing disease transmission. We illustrate our model with the examples of preexposure prophylaxis and community-based education compared with antiretroviral therapy for MSM in the US. We show both analytically and with the examples that HIV budgets are often best spent on the program that offers the greatest "bang for the buck.".

Keywords: Management Science and Engineering
Advisor: Brandeau Margaret L. primary advisor. Thesis advisor
Bendavid Eran advisor. Thesis advisor
Owens Douglas K. advisor. Thesis advisor