UC Davis

Understanding the fate and transport of nitrogen through the vadose zone is vital to reduce nitrate leaching, protecting groundwater quality, and enhancing resource use efficiency. Currently, there is limited data on the continuous monitoring of nitrate transport through the deep vadose zone. The lack of high-quality data makes it difficult to evaluate the effectiveness of conservation practices aimed at reducing nitrate leaching. The vadose-zone monitoring system (VMS) serves as an innovative technology for near real-time monitoring of nitrate and other contaminants as they travel through the shallow and deep vadose zone to groundwater. The objective of this study was to evaluate the performance of the VMS technology at three sites using bromide (Br-) as a tracer and the unsaturated flow model HYDRUS 1D to understand underlying vadose zone water flow and solute transport processes. Site 1 was a field crop site near Esparto, CA, with a heavy Capay-clay soil and a groundwater depth of approximately 10 m. Site 2 was an almond orchard near Modesto, CA, with a moderately homogenous sandy loam in the top 2 m and a sandy clay loam down to 6 m and a water table at approximately 8 m. Site 3 was a citrus orchard near Orange Cove, CA, with a sandy loam soil at the shallow depths (0-2 meters) followed by sandy clay loam down to 7 m and a groundwater depth of approximately 25 m. The VMS was installed at all sites to collect soil pore water samples at approximately 1 m intervals to about 7 m depth. To test the system performance, approximately 380 L of a 500 ppm Br- solution was applied as a conservative tracer at the three sites. The applied tracer was either percolated by rain, irrigation, or a combination of the two. The site HYDRUS models demonstrated a complete breakthrough of Br- at each vadose sampling port depth. Measured pore-water from the VMS exhibited similar solute breakthroughs with varying time and concentrations. The bromide tracer results confirm that the VMS is capable of monitoring flow and transport processes in the deep vadose zone.

In the first chapter, I contribute to the literature that studies academic impacts of disruptions due to weather or natural disasters. Such studies so far have mostly focused on younger children and evidence for older students is still limited. Furthermore, the wildfire landscape in California is characterized by frequent fires that burn close to the state's residential areas and their schools. I combine locations of the entire population of in-state wildfires with administrative school-level data to document the detrimental effects of wildfire exposure for older student academic achievement on standardized exams in public schools in California. I provide novel results for older students and I estimate implications of the physical presence of local wildfires, rather than smoke attributable to all wildfires in the U.S. as wildfire literature has done in the past. I find that local presence of large wildfires reduced mean test scores of boys by 0.05 standard deviations across all schools and by up to 0.15 standard deviations in rural socio-economically disadvantaged schools.

In the second chapter, we provide evidence to the discussion about the effect out-of-state university students have on potential in-state students. Despite paying a premium to attend state universities, researchers argue that out-of-state students may come at a cost to in-state students by negatively affecting academic quality or by crowding out in-state students. To study this relationship, we examine the effect of a 2016 policy at a highly ranked state flagship university that removed the limit on how many out-of-state students it could enroll. We find the policy caused an increase in out-of-state enrollment by around 29 percent and increased tuition revenue collected by the university by 47 percent. We argue that this revenue was used to fund increases in financial aid disbursed at the university, particularly to students from low-income households, indicating that out-of-state students cross-subsidize lower income students. We also fail to find evidence that this increase in out-of-state students had any effect on several measures of academic quality.

In the final chapter, we consider the early-1990s land protections covering tens of millions of acres of old-growth forest in the Northern Spotted Owl habitat in the U.S. Pacific Northwest and Northern California. In the intervening period, wildfire regimes in this region have become significantly more frequent, larger, and more severe. We find that these restrictions on timber harvesting lead to two outcomes. First, they caused an increase in the share of low-intensity wildfire ignitions by enhancing the natural shady and cool conditions of old-growth forests and their extensive tree canopies. At the same time, they ultimately greatly increased areas of wildfire perimeters that burned at high-severity in the protected forests---almost certainly because the logging restrictions encouraged accumulation of vegetation fuels. Severe wildfires often greatly harm affected ecosystems, and impose substantial economic costs on humans. We argue that qualified logging operations could serve a beneficial, complementary role to prescribed burns in forest management plans that aim to reduce wildfire severity.

Abstract

This research investigates the potential of Flame Spray Pyrolysis (FSP) as a technique for synthesizing Yttria-Stabilized Zirconia (YSZ) coatings on metal substrates with modified processing and thermal properties through doping. The aim is to explore how doping with Lanthanum (La) and Manganese (Mn) influences the microstructure and thermal conductivity of YSZ, a ceramic known for its high thermal stability and low thermal conductivity. This work is motivated by the need for low-cost and efficient thermal barrier coatings exploiting YSZ properties, which can be hypothetically enhanced through strategic doping.The study involves the preparation of 10YSZ structures doped with La and Mn and the application of those as coatings on aluminum disks using a custom-built FSP apparatus. This process includes optimizing parameters such as spraying distance and oxygen flow rate. The coatings’ crystalline structure and phase composition are analyzed using X-ray Diffraction (XRD), and Scanning Electron Microscopy (SEM) is used to assess the morphology of the nanostructures. Thermal conductivity is measured through Laser Flash Analysis (LFA). The results indicate that doping affects the deposition dynamics of YSZ. La doping results in better initial layer formation and deposition efficiency, while Mn doping influences the coating's adherence and increases the deposition rate over time. Both dopants alter the grain structure, impacting the physical and thermal properties of the coatings. The research hypothesizes that the ionic radii differences of La and Mn induce lattice distortions in YSZ, affecting its density and thermal conductivity.

This qualitative study explores the decision-making and navigation strategies of seven current women* leaders of campus-based Women, Gender, and Sexuality Centers (WGSCs) at large public research universities across the United States. With a feminist research design and an intersectional feminist lens, leaders illuminated their own personal transformational journeys as a driving force behind their commitment to equity and inclusion work. Recognizing foundational values and early experiences informs the ways they navigate their environments.

As pivotal hubs for gender equity initiatives, WGSCs also serve as platforms for fostering connections and facilitating collaboration, collective strategies, and partnerships. Drawing on a proposed Applied Critical and Intersectional Feminist Leadership framework, the analysis of findings revealed the innovative and unique insights for negotiating power and positionality within higher education institutions. Given the changing landscape within higher education, women’s center leaders draw upon their own survival strategies to harness solutions to our most complex problems today.

*women - all who experience life through the lens of woman in body, spirit, identity - past, present, future, and fluid (Gender Equity Resource Center, 2019)

Flaviviruses are arthropod-transmitted positive-sense single stranded RNA viruses, capable of causing significant human disease. Their RNA genomes are translated by host machinery and produce a viral polypeptide of 10 viral proteins, 3 structural and 7 non-structural. The non-structural proteins are essential for mediating virus genome replication, host defense silencing, and cell remodeling. Much of this is accomplished through physical interactions between viral protein and host proteins, which interrupts or otherwise impacts their cellular function for virus benefit. Inhibition of host protein function during these interactions can be connected to viral pathogenesis and disease. In the case of Zika virus (ZIKV) the primary disease outcome of concern is birth defects or fetal demise that occur in fetuses that are infected in utero via vertical transmission from the infected mother. Birth defects arising from ZIKV infection are broad and collectively termed congenital Zika syndrome (CZS). Most infamous of these is microcephaly, a condition where brain and head are not fully grown at birth. Microcephaly is associated with a wide range of debilitating development problems that last throughout life. The molecular mechanisms that contribute to microcephaly observed in CZS cases are not fully understood and likely multifactorial. To understand if ZIKV-host protein-protein interactions are contributing to neurodevelopmental defect, global proteomics was previously performed on ZIKV proteins to identify host interactors. This revealed the interaction between ZIKV non-structural 4A (NS4A) and the host protein ankyrin repeat and LEM domain containing 2 (ANKLE2). ANKLE2 is involved in nuclear envelope dynamics during mitosis and asymmetric cell division during neurogenesis, a key step in brain development. Mutations in ANKLE2 are associated with primary congenital microcephaly in humans. Expression of ZIKV NS4A in vivo results in abnormal brain development in fruit flies. This phenotype is rescued by overexpression of human ANKLE2. Together this data supports the hypothesis that NS4A physically interacts with ANKLE2, inhibiting its function during neurodevelopment to cause microcephaly. However, the basis for the physical interaction and the specific ways NS4A inhibits ANKLE2 function through it are still mysterious. Beyond this is the question of why NS4A interacts with ANKLE2 to begin with? Is the interaction, and the pathogenesis that follows, purely coincidental, or does NS4A interact with ANKLE2 to serve in some aspect of ZIKV replication? This work serves to explore the questions revolving the NS4A-ANKLE2 interaction. First, we establish that ANKLE2 has the opportunity to impact ZIKV replication by showing colocalization of ANKLE2 with ZIKV factors during virus replication. To explore if ANKLE2 is actively participating in some aspect of virus replication we then genetically deplete ANKLE2 using CRISPRi knockdown or CRISPR mutagenesis. Cells with diminished or depleted ANKLE2 were infected with ZIKV and had reduced replication across multiple conditions and cell lines. This work provides substantial evidence that ANKLE2 supports ZIKV replication in human cells. During a flavivirus transmission cycle the virus must efficiently replicate in both human and mosquito cells. In collaboration with another group, we show that depletion of the Ankle2 ortholog in mosquito Aag2 cells also leads to reduced ZIKV replication, supporting that Ankle2 is beneficial to virus replication across hosts. Further, we show that physical interaction between ANKLE2 and NS4A is conserved across four other mosquito-borne flaviviruses and that ANKLE2 plays a role in the replication of some of these viruses. In order to investigate the physical determinants of the ANKLE2-NS4A interaction we developed a series of truncation mutants that serially express fewer domains of each protein. To test physical interaction between the proteins, we performed co-transfection and co-immunoprecipitation experiments. This revealed the N-terminal region of ANKLE2 interacts with the C-terminal region of NS4A. Further, we show that this non-interacting ANKLE2 mutant does not colocalize with ZIKV NS4A during infection. However, the data suggest that there are multiple contact sites between ANKLE2 and NS4A, across separate domains. ANKLE2 is a scaffolding protein that modulates the cell cycle through physical protein interactions. To explore how these interactions may be perturbed during infection and how new interactions may be driven to benefit virus replication, we performed affinity-purification and mass spectrometry on ANKLE2 with and without ZIKV infection. These revealed hundreds of candidate protein interactions which enlighten both how ZIKV inhibits normal ANKLE2 function and also potential pathways through which ANKLE2 promotes virus replication. Altogether, this work vastly expands on our understanding of the ZIKV NS4A-ANKLE2 interaction and supplies avenues for future exploration.

Increasing reliance on wireless communication and complexity of cyberattacks have rendered industrial control systems (ICSs) such as process control systems (PCSs) (which are ICSs that operate chemical manufacturing processes) vulnerable to cyberattacks by malicious agents. In the past decade, several highly sophisticated cyberattacks (e.g., Stuxnet virus (2010), German steel mill attack (2014), Ukrainian power grid attack (2015), TRITON (2017)) have demonstrated that information technology (IT) infrastructure-based solutions to handling cyberattacks on control systems are insufficient on their own. An increasing body of research has focused on developing operational technology (OT)-based approaches to enhance the cyberattack resilience of PCSs. Cyberattack resilience here is defined as the ability of a PCS to minimize the impact of a cyberattack and recover from it. Research on cyberattack resilience of PCSs involves approaches that range from designing PCSs that are inherently attack-resilient to developing cyberattack detection, identification and mitigation schemes. Cyberattack detection schemes are OT-based anomaly detection schemes that reveal the presence of a cyberattack on a PCS by monitoring the process operational data for anomalies and are an important component of a cyberattack resilient PCS.

The motivating realization behind the work presented in this dissertation is that the influence of PCS design parameters may be exploited to reveal the presence of an ongoing cyberattack on a PCS. In the chapters that follow, several approaches for cyberattack detection are presented. First, a control screening approach that may be used to incorporate attack detectability within the conventional PCS design considerations is presented. The screening algorithm is based on a characterization of the interdependence between the PCS design parameters, and the ability of the detection scheme to detect the attack (attack detectability). Next, for a certain class of detection schemes monitoring a process, the relationship between the PCS design parameters, the closed-loop stability of the attacked process, and the detectability of certain attacks is rigorously characterized. Based on the characterization, for attack detection, it may be preferred to operate the process under performance degrading ``attack-sensitive'' parameters. To manage a potential tradeoff between attack detection and closed-loop performance, an active detection method utilizing switching between two control modes is developed. Under the active detection method, extended process operation is under a first (nominal) mode, the control parameters (called nominal parameters) for which are selected to meet traditional control design criteria. Under the second (attack-sensitive) mode, the process is operated with attack-sensitive parameters. The process is operated under the attack-sensitive mode intermittently to probe the process for an ongoing attack. Control parameter switching on a process under steady-state operation may induce transient behavior, which may trigger false alarms in the class of detection schemes. For processes with an invertible output matrix, a switching condition is imposed to select control parameter switching instances such that false alarms in the system are minimized.

To eliminate false alarms due to control switching on processes with a non-invertible output matrix, a reachable set-based detection scheme is developed. The reachable set-based cyberattack detection scheme guarantees a zero false alarm rate during transient attack-free process operation by tracking the evolution of the monitoring variable values with respect to their reachable sets of the attack-free process at each time step. Following this, a switching-enabled active detection method that utilizes the reachable set-based detection scheme to enable attack detection with a zero false alarm rate is presented. Furthermore, the control parameter switching instances between the nominal to attack-sensitive modes are randomized, thereby preserving the confidentiality of the detection method. Destabilization of a process for attack detection (as with operation under attack-sensitive mode) may not always be preferred. Two different alternate control modes that may be used to induce perturbations for active attack detection without destabilizing the attacked process are presented. To guarantee attack detection, the alternate control mode selected must induce ``attack-revealing'' perturbations in the process. Reachability analysis is used to present a set-based condition that if satisfied means that the control mode selected induces attack-revealing perturbations. Different models of false data injection attacks are considered. A screening algorithm that may be used to select an attack-revealing control mode for the active detection of attacks is presented. The application of all methods are applied to simulations of different illustrative processes to demonstrate their attack detection capabilities.

Without a precedent to laundering clothes off-Earth, a preliminary solution is required to develop a spaceflight laundry machine capable of operating in various gravity fields. With this thesis’ proposed solution, human exercise to power an agitating bladder, a closed-loop hydraulic system, and a wastewater sensor suite provide a desirable environment for quantifying waste-mass transfer away from textiles while minimizing textile damage. Bond Graph Theory is used to model the proposed solution and to evaluate how human-power and valve configurations affect the system’s cleaning performance. Bond Graph simulation results reveal preliminary performance metrics and hardware significantly impacting the machine’s performance. A human-powered laundry machine prototype and model are essential for maturing the technology to spaceflight readiness.

Numerical algorithm is a fundamental part of a chip and it plays a crucial rolein a chip. The efficient manipulation of numerical data is essential for achieving optimal performance and desired functionality of a chip. The algorithms are designed on the chip to solve complex mathematical problems in different fields. Therefore, an efficient and accurate numerical algorithm can improve the practicality of a chip. This paper presents some basic numerical algorithms that can apply to the target chip, and the target platform is Asynchronous Array of Simple Processors 3(AsAP3). The paper uses shift division as the basic dividing function throughout the algorithms to replace the traditional divisions. This paper implements Trigonometric functions, Exponential function, Natural Logarithm function, and LRN function on the AsAP3 platform. This paper applies Taylor series, CORDIC, and binary search algorithms to the implemented functions. Furthermore, this paper records the numerical results of these functions generated by AsAP3 and compares them with the reference values calculated by the MATLAB program. It analyzes the difference, SNR value, and throughput of simulated results to examine the accuracy of the calculation. The paper also displays difference and ratio graphs to visually present the magnitude of the difference. The results and comparisons show that the numerical algorithms offer a satisfactory performance in the target platform. The applications are programmed with C in Visual Studio and transferred to the AsAP3 platform. The comparison between the generated value and reference value is completed on MATLAB.

This thesis examines the application of model-free multi-agent reinforcement learning for autonomous model-free control and constrained optimization of process networks comprised of multiple interconnected processes. Initially, different types of multi-agent reinforcement learning algorithms are outlined, and the challenges faced in their implementation for process control are identified. Reinforcement learning is then combined with optimal control, where the reward function is designed based on quadratic penalty functions to improve computational time and achieve improved performance compared to sparse rewards proposed in previous research studies. Several multi-agent reinforcement learning strategies, including centralized, decentralized, and mixed-type (centralized action and decentralized execution) are considered and compared. An assessment of the benefits and drawbacks of each control strategy is presented. Finally, an evaluation of the robustness of the control system against parametric uncertainties and sensor noise which are of practical significance is given. Throughout the thesis, a model system comprising of two interconnected non-isothermal chemical reactors with a recycle stream and multiple reactions is used to illustrate the design and implementation of the reinforcement learning agents. The control objective is to regulate the reactors' temperatures and concentrations at desired set-points. The proposed framework can be applied to more general process networks.

In the last decade, the proliferation of online collaboration has vastly broadened the landscape of knowledge work. Individuals form online communities and accomplish complicated intelligent work together, such as developing software or planning healthy diets. These collaborations vary in levels of joint interaction and collaboration strategies, partially dependent on the technologies as well. While technological advancements have enabled large-scale flexible participation, they have also resulted in a proliferation of unorganized and overlapping knowledge contributions. Also, it may hinder misleading information from separating from credible knowledge. This over- whelming abundance and disorganization pose considerable challenges both for individuals and the community to leverage the knowledge to solve problems and make high-stakes decisions. These tasks demand not only cognitive resources but also advanced meta-cognitive skills. These obstacles highlight the need to concentrate on structures and distilling knowledge, from creation and integration to dissemination.

In my thesis, I explore the designs and understand the impacts of computational and visualizaion scaffolds that structure and highlight relevant and semantic knowledge, taking into account the socio-cognitive dynamics among collaborators. I aim to use technological support and social-cognitive mechanisms to mitigate cognitive and attentional limitations in online community-based cooperative work.

To help individuals actively explore and understand knowledge shared in online communities, such as videos, we first dive into the sharing from both video producers and audiences, and explore the idea of structuring semantic representations of video contents and audience comments, which aids in discerning high-quality videos and supports diverse video exploration compared to conventional video watching experiences. Empirical study results also illuminate the adoption and priority of structured overview for interpretation. Moving the understanding forward, accessing relevant knowledge doesn’t guarantee analysis and knowledge integration. We investigate social nudging approaches to scaffold engagement in higher-order thinking for high-stakes topic analysis, and compare the influences between common documentation tools and a concept- mapping-based space which also plays as thinking scaffold, DeepThinkingMap. Two lab studies reveal the effectiveness of social nudging in fostering both reflective and critical thinking, and confirmed the synergetic effect of nudging with other thinking scaffolds. Finally, we shift focus to synchronous video-based interactions and non-verbal cues. Our secondary analysis of group brainstorming sessions demonstrates the significant impact of metaphoric hand gestures on both individual and partner creativity and found that the positive effect of metaphoric gestures is independent of media richness of communication medium.

In conclusion, this dissertation underscores the potential of computational and social support in reshaping how knowledge is explored, integrated, and co-created within online communities. Based on the empirical findings about the socio-technical-cognitive mechanisms and the design space, this dissertation paves the way for future research that promotes organized, reflective, and efficient knowledge collaboration in online communities.