VictorJuiz/thesis huggingface dataset:
A Statistical Investigation of Species Distribution Models and Communication of Statistics Across Disciplines

Ecologists commonly make strong parametric assumptions when formulating statistical models. Such assumptions have sparked repeated debates in the literature about statistical identifiability of species distribution and abundance models, among others. Part I of this dissertation draws upon the econometrics literature to introduce a broader view of the identifiability problem than has been taken in ecological debates. In particular we use a simulation approach to illustrate the concepts of non-parametric and parametric identifiability and their implications for ecologists. The fact that all models are approximations has very different implications for these two cases of identifiability. When non-parametric identifiability holds, even a mis-specified parametric model provides a useful approximation to the truth, and the fit of alternative models can be compared. When non-parametric identifiability does not hold, parametric assumptions create artificial identifiability, and alternative models cannot be distinguished empirically./nJoint species distribution models (JSDMs) have become a popular tool for helping ecologists understand properties of a community while accounting for relationships between species. Part II of this dissertation stress tests a foundational JSDM to understand how well properties of the community are estimated in the presence of model mis-specification. Community diversity metrics summarize community characteristics that ecologists have historically been interested in, so it is of interest to ask whether estimation of these more complicated metrics is robust to inevitable model mis-specification./nBeing a statistician is a "hands-on" job that requires communicating with stakeholders and researchers in a variety of fields. Part III of this dissertation leverages the communication skills I have built while working at the intersection of ecology and statistics to teach statistics students how to write about statistical analyses in an accessible way that is still faithful to the data. A pedagogical approach is described that builds upon that of traditional writing and science communication. This approach adds to the solid foundation with concrete examples in the context of statistics, particular focus on the nuances of statistical language, and a focus on narrative that carries throughout the data analysis process itself.

Advisor: Fithian, William
de Valpine, Perry
Excitability of Sensory Cortex in Mouse Models of Fragile X Syndrome and Autism Spectrum Disorders

Distinct genetic forms of autism are hypothesized to share a common increase in excitation inhibition (E-I) ratio in cerebral cortex, causing hyperexcitability and excess spiking. We provide a systematic test of this hypothesis across 4 mouse models (Fmr1-/y, Cntnap2-/-, 16p11.2del/+, Tsc2+/-), focusing on somatosensory cortex. All mouse models with autism risk mutations showed reduced feedforward inhibition in layer 2/3 (L2/3) coupled with more modest, variable reductions in feedforward excitation, driving a common increase in E-I conductance ratio. Contrary to the classic, naïve prediction that increased E-I ratio drives spiking hyperexcitability, synaptic conductance modeling suggested that sensory inputs to this circuit would actually evoke stable or reduced firing in L2/3 in vivo. Indeed, spiking evoked by single whisker deflections was normal in the two strains whose modeling predicted stable synaptic depolarization (Cntnap2-/-, 16p11.2del/+) and was reduced in the Fmr1-/y mice, also matching that strain's modeling prediction. In addition, spiking of putative inhibitory neurons was reduced in each strain. Thus, increased E-I ratio does not necessarily yield increased spiking responses to simple sensory stimuli./nStable or reduced spiking was surprising given the dramatically reduced inhibition observed in each strain. Thus, we tested whether the Fmr1-/y mouse exhibits excess spiking in response to multi-whisker sequences, which drive more spiking in S1 compared to single-whisker deflections and may thus engage a different synaptic E-I ratio. Total spiking to whisker sequences, and cross-whisker suppression, were reduced in Fmr1-/y mice. These effects were explained by reduced firing to the anatomically corresponding columnar whisker and increased tuning heterogeneity within each cortical column. This suggests that weak or heterogeneous sensory maps may underlie circuit abnormalities in disorders expressing autism spectrum behaviors.

Advisor: Feldman, Daniel E
Urban greenhouse gas emissions from mobile and biogenic sources: An assessment using a high-density sensor network

The world’s cities account for up to 70 % of global carbon dioxide (CO2) emissions, while covering less than 2 % of the Earth’s surface. Achieving global goals of keeping temperature increases below 2° requires dramatic reductions in emissions. In keeping with this goal, cities around the world are implementing strategies to reduce carbon dioxide emissions. To support this effort, observations and analyses that assess attribution of emission reductions to specific mitigation strategies are needed. However, monitoring and attributing carbon dioxide emissions in cities are challenging since numerous emission sources are densely presented in cities with complex topography and turbulent mixing.In this dissertation, I present a novel approach to understanding urban carbon dioxide and to attribute emissions to specific source sectors using a near-surface, high-density urban monitoring network. The Berkeley Environmental Air-quality and CO2 Observation Network (BEACO2N) includes ~70 nodes in the San Francisco Bay Area distributed at ~2 km horizontal spacing. I show that the relationship between CO2 concentration and highway traffic flow is coherent throughout the network. Using a Gaussian plume model to represent the dispersion from the highways, I show that the observations constrain the decrease in emission rate per vehicle from 2017 to 2019. Increased fuel efficiency and electrification of the vehicle fleet are among the primary tools in California’s greenhouse gas reduction plan and this assessment suggest these plans are on track. Second, I leverage the Gaussian plume model to determine biogenic uptake of CO2 in the region. I find promising estimates of biogenic emissions that is comparable to the daily and seasonal estimates based on SIF Finally, I describe the implementation and evaluation of other trace gas sensors (O3, CO, NO, and NO2) for source attribution. I demonstrate the use of the relationship between trace gases that are co-emitted from combustion to characterize various emission sources.

Advisor: Cohen, Ronald C
Safe Real-World Autonomy in Uncertain and Unstructured Environments

We are captivated by the promise of autonomous systems in our everyday life. However, ensuring that these systems act safely is an immense challenge: introducing complex systems into real-world uncertain environments while guaranteeing safety at all times is impossible in applications like self-driving vehicles, collaborative factory robots, and assistive robots. These systems will inevitably need to make real-time decisions with limited computational resources, and incomplete knowledge of the environment and other agents. This dissertation is an effort towards achieving trustworthy real-world autonomy by enabling autonomous systems to:/n(1) make theoretical safety guarantees efficiently based on known information, and/n(2) bridge the safety gap between this theory and the real world by reasoning about uncertainty in the environment and other agents./nTowards this goal this dissertation covers various methods for scalable safety and real-time decision-making that draw from control theory, cognitive science, and learning, and are backed by both rigorous theory and physical testing on robotic platforms. We begin with an overview of reachability analysis and its applications for optimal control with safety guarantees. We then tackle the curse of dimensionality associated with reachability computation by decomposing systems or updating previous solutions in a warm-starting fashion. Next we explore planning in a simplified, low-dimensional space online with precomputed safety guarantees and tracking controls offline. This is extended to meta-planning, in which the online algorithm switches between faster/conservative modes and slower/accurate modes. Then we apply all of these tools towards navigating in uncertain environments among hard-to-predict agents such as human pedestrians. We use Bayesian machine learning methods to reason about human intention and navigate in a probabilistically safe manner. Finally, the dissertation ends with information about code bases and reachability tutorial examples.

Advisor: Tomlin, Claire J
Detection and Optimization Algorithms for Cyber-Physical Systems

Cyber-Physical Systems (CPS) play an ubiquitous role in operation and control in many different domains: power systems, finance, robotics, and automation. The complex interplay between cyber components such as software, communication protocols, computer servers and physical components, such as sensors and pieces of dedicated hardware, requires advanced and sophisticated methods and algorithms that ensure safe and efficient operation. In this thesis we tackle both safety and efficiency: We develop novel detection algorithms that are able to identify malicious attacks, sensor corruption and faulty measurements. Our detection mechanisms have provable guarantees based on rigorous asymptotic and non-asymptotic statistical analysis and can be readily implemented in CPS, such as robotic systems and autonomous vehicles. In addition, we developed collusion detection mechanisms that can be used to identify whether two or more CPS are colluding or not. We also design a mechanism that is able to induce selfish systems/agents to behave cooperatively. We showcase the performance of our algorithms with several different case studies. In our analyses, we place emphasis on algorithms that can be implemented in real-time, that is can be used while the system is under operation in the real-world. On the efficiency side, we developed real-time non-linear Model Predictive Control (MPC) Methods that can provide optimal solutions to the Optimal Control problem faced by the CPS during operation. Our algorithm exploits the control structure and is tailored for implementation in embedded hardware and can operate both with memory and computation time constraints. We showcase the performance of our algorithm with a C/C++ implementation and we compare to several current state-of-the-art Optimal Control solvers. We also extend our methodology to be used together with Pseudo-spectral Methods and Hybrid Systems, developing an integrated Mixed-Integer MPC algorithm that can handle complex non-linear dynamics and both continuous and discrete variables. With this thesis, our goal is to provide real-time practical algorithms that have provable guarantees in performance both in the detection task and in the optimal control task. Our algorithms are based on rigorous theoretical analysis and display very good performance and can be readily implemented in practical Cyber-Physical Systems.

Advisor: Aswani, Anil J
Measurement-based quantum feedback controls for quantum computation

The advance of experimental techniques in circuit quantum electrodynamics over last decadehas made it possible to monitor the evolution of qubits under continuous measurements in real time . This kind of measurements, as compared to the discrete ones, provides a stream of information for feedback to alter the system's quantum dynamics continuously in a desired manner, thus allowing broader possibilities. We obtain the information at a cost, the backaction on the states. However, the back-action turns out not to be just something disturbing and harmful to the control but instead can be harnessed, together with the control, to steer the system to our targets. This thesis discusses one such application, namely to use measurements to create entanglement from remote qubits under locally optimal control. It is illustrated that by carefully designing symmetric measurement and feedback operators, we can construct efficient Markovian or non-Markovian protocols which generate N-qubit W, general Dicke and Greenberger-Horne-Zeilinger states with high fidelity above 94% up to N = 100. In some cases, the fidelity even approaches unity. Following that, we describe how to take advantages of the continuous stream of information to protect the unitary dynamics of a quantum system subject to noises. We develop a practical protocol for continuous operation of a quantum error correcting code for protection of coherent evolution due to an encoded Hamiltonian against environmental errors, using the three qubit bit-flip code and bit-flip errors as a canonical example. We demonstrate, for both quantum memory and adiabatic Hamiltonians, that the protocol, once optimized, can significantly reduce logical errors with a performance which is close to the theoretical limit of the bit-flip code's capability. In the adiabatic Hamiltonian case, we also propose some novel correction operators instead of the conventional ones to further reduce the logical errors.

Advisor: Whaley, Birgitta
Discrete and Complex Algorithms for Curves

This dissertation consists of two parts. The first part pertains to the Schottky problem, which asks to characterize Jacobians of curves amongst abelian varieties. This has a complete solution only in the first non-trivial case where the genus is four, and the solution is described in terms of the Riemann theta function. We first present a Julia package for numerical evaluations of the Riemann theta function. We then describe numerical approaches to the Schottky problem in genus four and five. We present a solution to a variant of the Schottky problem in genus five, for Jacobians with a vanishing theta null. Finally, we describe solutions to the tropical Schottky problem, and relate the tropical and classical solutions to the Schottky problem in genus four./nThe second part of this dissertation relates to cryptography. We first study cycles of pairing-friendly elliptic curves, for an application in pairing-based cryptography. We next study the concrete security of the Learning With Errors problem in lattice-based cryptography, when sampling the secret from a non-uniform, small distribution.

Advisor: Sturmfels, Bernd
Chiesa, Alessandro
Guts, Dehn Fillings and Volumes of Hyperbolic Manifolds

We construct an invariant called guts for second homology classes in irreducible 3-manifolds with toral boundary and non-degenerate Thurston norm. We prove that guts of second homology classes in each Thurston cone are invariant under a natural condition. We show that the guts of different homology classes are related by sutured decompositions. As an application, an invariant of knot complements is given and is computed in a few interesting cases./nThe minimal volume of orientable hyperbolic manifold with a given number of cusps has been found for 0,1,2,4 cusps, while the minimal volume of 3-cusped orientable hyperbolic manifolds remains unknown. By using guts in sutured manifolds and pared manifolds, we are able to show that for an orientable hyperbolic 3-manifold with 3 cusps such that every second homology class is libroid, its volume is at least 5.49... = 6 times Catalan’s constant./nIn the final chapter, we develop a method for controlling the upper bound of the Euler characteristic of surfaces in sufficiently long Dehn fillings. By using this method, we show that for a compact orientable irreducible acoannular 3-manifold with toral boundary, properly norm-minimizing surfaces capped off with disks in sufficiently long fillings are still properly norm-minimizing. We also show that if a sufficiently long Dehn surgery on a link in a product sutured manifold yields the same product sutured manifold, then this link is horizontal in the product sutured manifold. Combining these results, we prove that for a compact orientable irreducible acoannular 3-manifold with toral boundary, the cores of its sufficiently long fibered Dehn fillings are either horizontal or vertical. Moreover, we provide a new way to prove that there are finitely many links with a given complement such that no component is unknotted and no 2-component sublink is coaxial. Another result coming from this method is that all sufficiently long fillings of an orientable, irreducible, boundary-irreducible-irreducible, acoannular 3-manifold with toral boundary are still irreducible, boundary-irreducible-irreducible, acoannular.

Advisor: Agol, Ian
Plants on the move: the biogeography of dispersal and persistence under climate change

This dissertation explores how climate shapes plant biogeography, and the implications for plant vulnerability in the face of ongoing climate change. Climate structures plant biodiversity patterns across biotic scales ranging from genes to species to biomes, not only by influencing plant physiology and its many downstream effects, but also by influencing plant movement through the transport of seeds, pollen, and spores by wind. Understanding these phenomena is a core goal in plant ecology, and has become an increasingly urgent societal priority as accelerating anthropogenic climate change threatens biodiversity and ecosystem services across the world. Focusing on large spatial scales, this dissertation research investigates three connected facets of climate biogeography. The three chapters proceed down a hierarchy of concepts, each focusing more narrowly and deeply on one aspect of the preceding chapter; the focal level of biotic organization narrows in tandem, beginning with a study of vegetation formations in the first chapter and ending with an analysis of genetic loci in the third. Chapter 1 begins broadly, developing a framework for integrating three previously separate paradigms of ecological vulnerability to climate change, and using this framework in a large-scale spatial analysis of vegetation vulnerability across the western US. Chapter 2 focuses on one of these three paradigms, spatial novelty, which addresses dispersal limitation under climate change. Many plant species disperse by wind, and this new conceptual and modeling work provides the first global assessment of how wind patterns may shape range shifts and gene flow as climate warms. In chapter 3, this focus on wind dispersal is further narrowed to an investigation of wind’s role in shaping landscape genetic patterns in trees. This study reanalyzes population genetic data from more than a hundred tree species worldwide using the wind connectivity models developed in chapter 2, and shows for the first time that wind shapes directional gene flow, genetic differentiation, and genetic diversity. In sum, these analyses each advance our understanding of how climate influences basic spatial ecology, while also developing concepts and tools that may help land managers and conservation practitioners hone strategies for adaptation to global environmental change.

Advisor: Ackerly, David D
Strategies for High-Resolution Investigation of Bacterial Ribosome Function by Cryo-Electron Microscopy

This dissertation comprises projects focused broadly on cryo-electron microscopy (cryo-EM) methods and their application to high-resolution structural biology of the ribosome. The ribosome is the cell’s machinery for creating proteins in a series of steps referred to as translation. During translation, the large and small subunits of the ribosome participate in a cyclical process of association and disassociation, complexing with messenger RNAs, transfer RNAs, and many other translation factors along the way. From the intricacy of this process and of the ribosome itself comes a high degree of efficiency and fidelity in the synthesis of polypeptides. Structure is at the core of our current (and evolving) understanding of how the ribosome accomplishes this feat. Structures of the ribosome specifically are also rich with information implicating the fundamentals of RNA structure and folding, ribosomal assembly, medicine, and evolutionary relationships./nMuch of what has historically made an ideal specimen for single-particle cryo-EM is embodied by the ribosome: it is large, measuring approximately 25 nm in diameter and weighing approximately 2.6 MDa in bacteria, and it displays conformational flexibility that is difficult to capture and resolve by other methods. The recent widespread use of direct electron detectors has pushed the limits of what is achievable by single-particle cryo-EM, whose development over the past several decades has been punctuated by important advances involving the ribosome. Herein are described multiple stories from both sides of the coin – cryo-EM and ribosomal biology – including the most well-resolved ribosome structure to date, whose global resolution broke the 2 Å barrier for the first time for a large ribosomal subunit. Concluding thoughts consider future directions for cryo-EM methods development, informed by a specialized focus on the ribosome during a period of rapid growth in the field.

Advisor: Cate, Jamie H. D.
Heirloom Wearables: A Hybrid Approach to the Design of Embodied Wearable Technologies

Device miniaturization and new materials have enabled wearable technology to be integrated more seamlessly with the body, leveraging form factors such as clothing, jewelry, temporary tattoos, and beyond. While adopting familiar forms, many of these new technologies inherit interaction modalities and usage patterns from existing technologies (e.g. Smartphones), rather than being inspired by the rich cultural history and connotations of the form factor itself. In this thesis, I motivate the unique opportunities that arise when incorporating existing practices and cultural meaning into the design of wearable technologies./nI define a new class of wearable technologies that adopt existing form factors, leveraging well-established body practices and traditions -- Heirloom Wearables. I argue that this class of wearable technologies can foster meaningful relationships with technology on the body that more closely resemble experiences with traditional body-worn artifacts than modern wearable technologies. I present a lightweight framework to facilitate the design of Heirloom Wearable technologies, and detail five exemplar prototypes designed to operationalize the framework: fingernail-worn devices, interactive hair, dynamic clothing & accessories, interactive hats, and lotion interfaces. The concept of Heirloom Wearables, the framework, and the exemplar prototypes demonstrate how the limitations and constraints of body-based technologies can be transformed into opportunities for design, and highlight how body-centric practices can inform new and embodied wearable technologies./nAs a result, this work contributes a design methodology towards a more diverse range of inclusive wearable technologies. This new landscape of devices blurs the distinction between modern wearable technologies and traditional body-worn artifacts, fostering meaningful and intimate relationships with technology on the body.

Advisor: Paulos, Eric