VictorJuiz/thesis huggingface dataset:
Ecosystem assembly in California [electronic resource] : linking pattern to process at the landscape scale

The processes controlling ecosystem assembly are diverse and interacting. While landscape ecologists and geographers tend to focus on the relationships between plants and the environment in space ('environmental filtering'), community ecologists often emphasize species interactions over time ('competition', 'migration', 'facilitation'). Here I integrate concepts from community and landscape ecology with geostatistics and data from the Carnegie Airborne Observatory to better understand what observed patterns in vegetation can tell us about ecosystem assembly processes. This work took place in two California ecosystems, where the mediterranean-type climate has helped to generate a distinct mosaic of grassland, shrubland, and forest. Chapter 1 focuses on understanding controls on aboveground biomass (AGB) in a small protected area (Jasper Ridge Biological Preserve, Woodside, CA). One conclusion from this work is that mapped environmental gradients were not the clear dominant drivers of AGB patterns, suggesting that dynamic processes like disturbance, dispersal limitation, and limits to establishment may be critical drivers of patterns in this system. Chapter 2 explores the controls on greenness and vegetation structure on a much larger scale (Santa Cruz Island, Santa Barbara County, CA). I show that environmental gradients do explain some of the variation in this recently disturbed landscape, but that grazing intensity and spatial autocorrelation are also important predictors. Chapter 3 returns to Jasper Ridge to consider the links between plant functional types, foliar chemistry, and environmental gradients. I conclude that at the landscape scale environmental filtering can explain some of the observed patterns in chemical traits, but that researchers' efforts to confirm or eliminate possible explanations for observed trait patterns are likely closely tied to the specific ecosystem or community in which they are tested, and results can vary even within a single landscape.

Keywords: Biology.
Advisor: Asner Gregory P. primary advisor. Thesis advisor
Field Christopher B.
Mooney Harold
Vitousek Peter Morrison advisor. Thesis advisor
The effect of upstream perturbations on 3D annular diffusers [electronic resource]

This study investigated annular diffuser sensitivity to varying inlet perturbations similar to those found in turbine exhaust diffuser applications. The diffusers had a range of opening angles and contained airfoil shaped struts. The full 3D velocity field was measured using Magnetic Resonance Velocimetry and pressure measurements were acquired with static wall pressure taps. Additionally, the inlet turbulence was characterized using hotwire anemometry. The overall goal was to better understand how to design diffusers which would give high performance without excess sensitivity to highly variable inlet conditions. Three diffusers were investigated which each had a single expanding wall at the outer radius with a high expansion angle for the front half of the diffuser and a lower expansion for the downstream half. The initial expansion angles were 12 deg, 16 deg and 20 deg and the back angle was 6 deg for all three cases. These expansion angles resulted in exit area ratios of 1.21, 1.29 and 1.34, respectively. There was a full annulus model with five struts and a higher resolution one-fifth annular sector with a single strut for each diffuser. Five inlet conditions were investigated; a baseline case with a nominally uniform inlet, thin boundary layers and around 3% turbulence intensity, a high turbulence case that was similar to the baseline case except it had approximately double the turbulence intensity, a hub-strong case with a negative radial velocity gradient, a case with a high velocity wall jet at the outer radius, and a case with swirling inlet flow. The conservative diffuser with the 12 deg initial expansion angle was robust under the inlet conditions investigated. There was little variation in the integral parameters from one inlet condition to another and it had the lowest overall loss coefficient ranging from 0.35 to 0.40. This diffuser did not stall although there were small regions of reverse flow in the corners between the expanding wall and the strut with the swirl inlet. The pressure recovery coefficient for this diffuser ranged from 0.24 to 0.31. The moderate diffuser with the 16 deg initial expansion angle had substantial variation in the integral parameters depending on the inlet condition. The diffuser stalled and had high losses with the uniform inlet while the tip jet case had no reverse flow except in the wake of the strut and had the highest pressure recovery coefficient of all of the cases (0.35). The aggressive diffuser with the 20 deg initial expansion angle was robust in that it always stalled but there was still substantial variation in the integral parameters. The blockage and outlet distortion changed greatly depending on the inlet condition similar to the range of variation for the moderate diffuser. The aggressive diffuser with the hub-strong inlet had the highest loss coefficient and the lowest pressure recovery for all of the cases investigated.

Keywords: Mechanical Engineering
Advisor: Eaton John K. primary advisor. Thesis advisor
Iaccarino Gianluca advisor. Thesis advisor
Santiago Juan G. advisor. Thesis advisor
Effects of recent evolution on the genetic basis of human disease [electronic resource]

In the last 100,000 years, humans have been subjected to multiple different evolutionary pressures. Migration events, changing food sources, climate change, and technological advances are some of the ways environmental changes have applied pressure on human populations to undergo change. Recent advances in methods to measure differences in DNA sequences have led to new powerful techniques to measure the effect of evolution on different human populations. Also due to the availability of recent explosion of genomic data, our understanding of genetic basis of human disease has grown significantly. However, our knowledge regarding the effect that recent evolution has had on the genetic susceptibility to disease has grown to a much lesser extent. There is a lack of studies attempting to place the genetic basis of disease in the context of recent evolutionary changes. I describe multiple ways in which recent evolutionary pressures on the human genome can lead to insights to understanding how evolution has impacted complex disease. I show that GWAS (Genome-Wide Association Studies) are particularly well suited to measure the effect of recent evolution in complex disease. I provide methodology to detect positive selection in human disease and are able to ascertain whether recent evolution has disproportionately increased or decreased the risk of inherited disease. In addition, I introduce a method to approximate when and where genetic risk differentiation for specific disease has occurred, starting when humans began migration out of Africa. Environmental changes in the last 10,000 years known to have created novel, diverse, and pervasive pathogens. I provide methodology to find positive selection in communicable disease. I identify populations that have most likely been severely impacted by specific pathogens in recent human history. I develop and apply methods to identify specific genetic variants important to both communicable and inherited disease that have been affected by evolutionary pressures. I find that type 1 diabetes has recently undergone strong positive selection towards increasing genetic risk in European derived populations. In addition type 2 diabetes and pancreatic cancer is associated with migration trajectories and I find genetic risk differentiation exceeding what is expected by genetic drift in a total of 11 complex diseases. Finally, I find evidence of positive selection in many distinct populations within proteins interacting bacillus anthracis and yersinia pestis, which cause anthrax and the bubonic plague, respectively. I have shown how recent evolution can lead to an increased understanding of both inherited and infectious disease.

Advisor: Butte Atul J. primary advisor. Thesis advisor
Ashley Euan A. advisor. Thesis advisor
Batzoglou Serafim
Bustamante Carlos (Carlos D.)
Effects of Supersonic Relative Velocity Between Baryons and Dark Matter in the Early Universe

Evolution of the Universe following cosmic recombination is typically modeled only in linear approximation. Tseliakhovich and Hirata (2010) showed that supersonic bulk relative velocity between cold dark matter and baryonic matter, coherent over scales of tens to hundreds of comoving Mpc, produces important nonlinear effects during this era. We present a new pseudo-spectral simulation code, which is uniquely able to model the nonlinear evolution of the matter density fields beginning at recombination. Using this code, we investigate the relative-velocity effect and quantify the suppression of structure formation on small scales. We demonstrate that the effect is present even by redshift z ~ 400. By z ~ 100, baryonic power has been suppressed by around 40% at scales of k = 80 h/Mpc, as compared with the standard linear theory.

Keywords:  Department of Physics
early Universe
nonlinear evolution models
Thesis
Advisor: Wechsler Risa
Abel Tom
The effects of team member intrinsic differences on emergent team dynamics and long-term innovative performance in engineering design teams [electronic resource]

An increasing amount of work and learning takes place in a team context. Corporations rely on multidisciplinary teams to create innovative products, and team-based education is becoming an established and widespread practice. But what really makes for a great team? How do we put teams together, and how can we guarantee that they will be effective? Moreover, how can we encourage those teams to be more creative in their problem-solving? In many ways, we lack standard measurements of these individual aspects (e.g. there is no single accepted measure for team performance) and we also lack a holistic model describing the interplay between these aspects. This study takes a particular focus on design engineering teams working to develop innovative solutions to challenging multidisciplinary problems. Prior research informs us that intrinsic functional diversity can create the precondition for constructive task-based conflict within the team, contributing to an increased likelihood of innovative outcomes. However, diversity is also known to have mixed and often negative effects on team function, particularly at the level of emergent team phenomena such as conflict and communication (broadly defined as the team dynamic). A coherent model is needed to understand how intrinsic compositional aspects reliably impact team dynamics, and ultimately, how the team dynamics and underlying compositional characteristics interact to affect performance. A methodology is presented that attempts such an end-to-end description of team composition, dynamics and performance, principally relying on the Wilde Type indicator as a measurement of intrinsic differences. Results support the use of this instrument at the individual and team level, as well as offering insight into the impact of composition and diversity on team dynamics, and the ultimate effects on performance. Opportunities are explored for improved interventions in the team dynamic on the basis of these results.

Keywords: Mechanical Engineering
Advisor: Leifer Larry J. primary advisor. Thesis advisor
Cutkosky Mark R. advisor. Thesis advisor
Steinert Ralf
Wilde Douglass J. advisor. Thesis advisor
Efficient algorithms for collaborative filtering [electronic resource]

Collaborative filtering is a novel statistical technique to obtain useful information or to make predictions based on data from multiple agents. A large number of such datasets are naturally represented in matrix form. Typically, there exists a matrix M from which we know a (typically sparse) subset of entries M_ij for (i, j) in some set E. The problem then is to predict/approximate the unseen entries. This framework of matrix completion is extremely general and applications include personalized recommendation systems, sensor positioning, link prediction and so on. Low rank models have traditionally been used to learn useful information from such datasets. Low-dimensional representations simplify the description of the dataset and often yield predictive powers. As an added benefit, it is easier to store and retrieve low dimensional representations. Finally, many computationally intensive operations such as matrix multiplication and inversion are simplified with low dimensional representations. Singular Value Decomposition (SVD) has traditionally been used to find the lowdimensional representation of a fully revealed matrix. There are numerous algorithms for computing the SVD of a matrix including several parallel implementations and implementations for sparse matrices. However, when the matrix is only partially observed, we show that SVD techniques are sub-optimal. In this work, we will develop algorithms to learn a low rank model from a partially revealed matrix. These algorithms are computationally efficient and highly parallelizable. We will show that the proposed algorithms achieve a performance close to the fundamental limit in a number of scenarios. Finally, the algorithms achieve significantly better performance than the state-of-the-art algorithms on many real collaborative filtering datasets.

Keywords: Electrical Engineering
Advisor: Boyd Stephen P. primary advisor. Thesis advisor
Montanari Andrea primary advisor. Thesis advisor
Van Roy Benjamin advisor. Thesis advisor
Efficient methods for the study of subcontinental structure in admixed populations [electronic resource]

The central theme of this work revolves around the genetics of admixed individuals---individuals who derive their ancestry from two or more different ancestral populations.The genomes of admixed individuals exhibit unique properties that make them both fascinating and challenging to study using existing statistical methods. Their uniqueness lies in their block-like structure, a feature that is the direct result of generations of recombination events. An important advance in the field of admixture genetics has been the development of algorithms capable of determining the ancestry of different regions in the admixed genome. As we will illustrate in this work, local ancestry information can readily be harnessed towards the investigation of subcontinental structure, by which we attempt to determine the specific ancestral populations that gave rise to the admixed genomes under study, and whether differences exist in the ancestral makeup of these admixed samples. The latter line of investigation is of particular relevance to genome-wide association studies, which are prone to confounding if structure in a population has not been explicitly corrected for. This work is thus divided into three parts. We first apply some straightforward multivariate statistical methods such as PCA to gain insights into the African ancestry of African Americans. To this end, we introduce a novel method for the study of specific components of admixture in admixed individuals. We then expand on this work to introduce more sophisticated algorithms for the study of admixed genomics. These methods entail the development of an improved method for local ancestry deconvolution, and the implementation of a PCA approach designed to handle large amounts of missing data. We illustrate the power of using these methods in conjunction with one another with the study of two Latino populations. Finally, we describe a novel phasing algorithm designed to incorporate sequencing information into the process of haplotype reconstruction---an important upstream step for many of the analyses described here.

Keywords: Genetics
Advisor: Bustamante Carlos (Carlos D.)
Montgomery Stephen
Sherlock Gavin advisor. Thesis advisor
Sidow Arend advisor. Thesis advisor
Efficient microarchitecture for network-on-chip routers [electronic resource]

Continuing advances in semiconductor technology, coupled with an increasing concern for energy efficiency, have led to an industry-wide shift in focus towards modular designs that leverage parallelism in order to meet performance goals. Networks-on-Chip (NoCs) are widely regarded as a promising approach for addressing the communication challenges associated with future Chip Multi-Processors (CMPs) in the face of further increases in integration density. In the present thesis, we investigate implementation aspects and design trade-offs in the context of routers for NoC applications. In particular, our focus is on developing efficient control logic for high-performance router implementations. Using parameterized RTL implementations, we first evaluate representative Virtual Channel (VC) and switch allocator architectures in terms of matching quality, delay, area and power. We also investigate the sensitivity of these properties to key network parameters, as well as the impact of allocation on overall network performance. Based on the results of this study, we propose microarchitectural modifications that improve delay, area and energy efficiency: Sparse VC allocation reduces the complexity of VC allocators by exploiting restrictions on transitions between packet classes. Two improved schemes for speculative switch allocation improve delay and cost while maintaining the critical latency improvements at low to medium load; this is achieved by incurring a minimal loss in throughput near the saturation point. We also investigate a practical implementation of combined VC and switch allocation and its impact on network cost and performance. The second part of the thesis focuses on router input buffer management. We explore the design trade-offs involved in choosing a buffer organization, and we evaluate practical static and dynamic buffer management schemes and their impact on network performance and cost. We furthermore show that buffer sharing can lead to severe performance degradation in the presence of congestion. To address this problem, we introduce Adaptive Backpressure (ABP), a novel scheme that improves the utilization of dynamically managed router input buffers by varying the stiffness of the flow control feedback loop based on downstream congestion. By inhibiting unproductive buffer occupancy, this mitigates undesired interference effects between workloads with differing performance characteristics.

Keywords: Electrical Engineering
Advisor: Dally William
Kozyrakis Christoforos
Olukotun Oyekunle Ayinde advisor. Thesis advisor
Efficient, stable locomotion in legged robots [electronic resource]

Legged animals have explored more of the Earth's surface than any human designed vehicle. The agility, adaptability, and efficiency found in nature continues to inspire robotics researchers to develop efficient leg designs robust, stable and adaptable control strategies that can rapid changes in the environment. Understanding the dynamics of ground collision and contact is critical to advancing the state of the art of legged robotics and allowing legged robotics to narrow the performance gap with legged animals. Unfortunately modeling the dynamics of collision requires attention not just to whole cycle measures like the coefficient of restitution but also to the transient measures of slip and initiation of chatter. This thesis contributes to the model-based design and control of legged robots by developing compliant contact models for systems where the deformation of the contact bodies is small and the contact forces can be considered to act through a single point. A novel visco-plastic contact model is developed to represent collision dynamics during legged locomotion. The relationship between the model's damping parameter and the coefficient of restitution is formulated using the energetic coefficient which permits energy consistent formulation for collisions that are non-collinear and include slip reversal. Given experimental data of the position and force of the foot, the model parameter estimation is performed with an offline genetic algorithm and an online unscented Kalman filter. The effectiveness of the methods are demonstrated on one-dimensional collisions of a single mass and a mass spring damper system. The methods presented allow for a physics-based study of the effect of leg and foot compliance on the energy efficiency of legged locomotion and of locomotion controllers. An actuated, non conservative, continuous contact SLIP model is developed for greater analysis of dynamics of running. Methodologies for finding passive (and active) gait controllers are of great interest to robotics but for non-conservative models, there are no passively stable fixed points around which to build such controllers. Minimal heuristic controllers are generated for bouncing gait generation which allow for stable hopping in the presence of actuator and ground contact energy losses. Together with the online inverse model parameter estimation, the approach advances robotics toward realizing adaptive optimal efficiency locomotion based on terrain measurements.

Keywords: Mechanical Engineering
Advisor: Waldron Kenneth J. primary advisor. Thesis advisor
Cutkosky Mark R. advisor. Thesis advisor
Gerdes J. Christian advisor. Thesis advisor
An egalitarian theory of the rule of law [electronic resource]

This dissertation offers a new theory of the rule of law, its moral value and what it requires of states. It argues that the rule of law is required for states to treat citizens as equals, not, as conventionally understood, to guarantee citizens' liberty. This claim is defended as part of a coherentist account of the rule of law, where the normative argument and the conceptual argument (about the demands of the rule of law) depend on one another, and draw from our understanding of real-world states. Chapter one defends the egalitarian account of the rule of law. Chapter two criticizes the traditional account, on which the rule of law responds to citizens' interests in individual liberty. Chapter three demonstrates the application of this theory to classical Athens. Chapter four demonstrates its application to the United Kingdom.

Keywords: Political Science
Advisor: Cohen Joshua
Fearon James D. advisor. Thesis advisor
Greif Avner
Ober Josiah advisor. Thesis advisor